LncrRNA and mRNA expression profiling in human esophageal squamous cancer
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE89102 | GEO | 2016/10/25
SECONDARY ACCESSION(S): PRJNA350289
REPOSITORIES: GEO
Similar Datasets
Project description:miRNAs comprise a family of small non-coding RNA molecules that have emerged as key post-transcriptional regulators of gene expression. Aberrant miRNA expression has been linked to various human tumors. This study was aimed to identify new aberrant expression miRNA in esophageal squamous cell carcinoma (ESCC) and invested the potential functions in this tumor. miRNA microarray analysis with 4 ESCC and adjacent non-tumor tissues was performed.
2014-09-18 | E-GEOD-61047 | biostudies-arrayexpress
Project description:miRNAs comprise a family of small non-coding RNA molecules that have emerged as key post-transcriptional regulators of gene expression. Aberrant miRNA expression has been linked to various human tumors. This study was aimed to identify new aberrant expression miRNA in esophageal squamous cell carcinoma (ESCC) and invested the potential functions in this tumor.
2014-09-18 | GSE61047 | GEO
Project description:Systems biology approaches can help understand pathogenesis of complex human diseases like cancers for identification of potential new therapeutic targets. Here in this study, we performed genome-wide screening for mRNA and lncRNA profiles in esophageal cancer to identify the novel cancer-related mRNA and lncRNA in esophageal squamous cell carcinoma (ESCC). We identified 3000 up-regulated/2517 down-regulated mRNAs and 402 up-regulated/741 down-regulated lncRNAs. Further functional analysis revealed differentially expressed genes (DEGs) of mRNA and lncRNA are related to different pathways. mRNA pathways are mainly involved in cell cycles while lncRNA pathways are for regulation and metabolic procession. Differentially expressed mRNAs/lncRNAs were validated with qPCR. At last, mRNA and lncRNA co-expression network were built and highly-connected networks were identified, which may provide a mechanism of mRNA expression regulation by lncRNA. To our knowledge, this is the first study to explore the co-expression networks and the lncRNA-mRNA networks could be therapeutic targets for ESCC treatments.
2019-02-23 | GSE111011 | GEO
Project description:Background & Aims: Esophageal squamous cell carcinoma (ESCC) is believed to arise from esophageal mucosa through accumulation of both genetic and epigenetic changes. DNA methylation is a critical epigenetic mechanism involved in key cellular processes and its deregulation has been linked to many human cancers, including ESCC. The aim of this study is to examine the global deregulation of methylation states in ESCC and identify potential early biomarkers. Conclusions: This is the first study to address methylation changes in ESCC in a large panel of genes. Methylome analysis is shown as a sensitive and powerful tool to identify molecular players in ESCC. These data should prove to be the reference for future studies identifying potential biomarkers and molecular targets of ESCC. We performed a bead array analysis of more than 800 cancer-related genes in a series of 10 ESCC samples, 10 matched surrounding tissues, and 4 esophageal mucosa from healthy individuals. Pyrosequencing was used for validation of DNA methylation changes in up to 106 patients and 27 controls.
2011-11-23 | E-GEOD-26784 | biostudies-arrayexpress
Project description:Preoperative chemoradiotherapy (CRT) followed by surgery has been proved to improve esophageal squamous cell carcinoma (ESCC) patientsM-bM-^@M-^Y survival in comparison with surgery alone. However, the outcomes of CRT are heterogeneous, and no clinical or pathological method could predict CRT response. We aim to identify mRNA markers for ESCC CRT-response prediction through gene expression analyses. Gene expression analyses were performed on pretreatment cancer biopsies from 28 ESCCs who received neoadjuvant CRT and surgery and 10 normal esophageal epithelia using Affymetrix U133 Plus 2.0 arrays.
2014-08-01 | E-GEOD-45670 | biostudies-arrayexpress
Project description:Objective: Globally, esophageal cancer is among the most deadly cancer forms. Long non-coding RNAs (lncRNA) are frequently found to have important regulatory roles. We aim to assess the lncRNA expression profile of esophageal squamous cell carcinoma (ESCC) and identify prognosis related lncRNAs. Design: LncRNA expression profiles were studied by microarray in paired tumor and normal tissues from 119 ESCC patients, and validated by qRT-PCR. The 119 patients were subsequently divided randomly into training (n=60) and test (n=59) groups. A prognostic signature was developed from the training group using a random forest supervised classification algorithm and a nearest shrunken centroid algorithm, and validated in test group and further in an independent cohort (n=60). The independence of the signature in survival prediction was evaluated by Multivariable Cox regression analysis. Results: LncRNAs showed significantly altered expression in ESCC tissues. From the training group, we identified a three-lncRNA signature (including the lncRNAs ENST00000435885•1, XLOC_013014, and ENST00000547963•1) which classified the patients into two groups with significantly different overall survival (median survival 19•2 months vs. not reached, p<0•0001). The signature was applied to the test group (median survival 21•5 months vs. not reached, p=0•0030) and independent cohort (median survival 25•8 months vs. not reached, p=0•0187) and showed similar prognostic values in both. Multivariable Cox regression analysis showed that the signature was an independent prognostic factor for ESCC patients. Stratified analysis suggested that the signature was prognostic within clinical stages. Conclusions: Our results suggest that the three-lncRNA signature can serve as a novel biomarker for the prognosis of ESCC patients. Application of it allows for more accurate survival prediction. The lncRNA expression profiles of cancer and adjacent normal tissues form 119 ESCC patients were studied by microarray and an lncRNA signature that can perdict the survival of ESCC patients was identified.
2014-03-07 | E-GEOD-53624 | biostudies-arrayexpress
Project description:Objective: Globally, esophageal cancer is among the most deadly cancer forms. Long non-coding RNAs (lncRNA) are frequently found to have important regulatory roles. We aim to assess the lncRNA expression profile of esophageal squamous cell carcinoma (ESCC) and identify prognosis related lncRNAs. Design: LncRNA expression profiles were studied by microarray in paired tumor and normal tissues from 119 ESCC patients, and validated by qRT-PCR. The 119 patients were subsequently divided randomly into training (n=60) and test (n=59) groups. A prognostic signature was developed from the training group using a random forest supervised classification algorithm and a nearest shrunken centroid algorithm, and validated in test group and further in an independent cohort (n=60). The independence of the signature in survival prediction was evaluated by Multivariable Cox regression analysis. Results: LncRNAs showed significantly altered expression in ESCC tissues. From the training group, we identified a three-lncRNA signature (including the lncRNAs ENST00000435885•1, XLOC_013014, and ENST00000547963•1) which classified the patients into two groups with significantly different overall survival (median survival 19•2 months vs. not reached, p<0•0001). The signature was applied to the test group (median survival 21•5 months vs. not reached, p=0•0030) and independent cohort (median survival 25•8 months vs. not reached, p=0•0187) and showed similar prognostic values in both. Multivariable Cox regression analysis showed that the signature was an independent prognostic factor for ESCC patients. Stratified analysis suggested that the signature was prognostic within clinical stages. Conclusions: Our results suggest that the three-lncRNA signature can serve as a novel biomarker for the prognosis of ESCC patients. Application of it allows for more accurate survival prediction. The lncRNA expression profiles of cancer and adjacent normal tissues form 119 ESCC patients were studied by microarray and an lncRNA signature that can perdict the survival of ESCC patients was identified.
2014-03-07 | E-GEOD-53622 | biostudies-arrayexpress
Project description:Our aim is to identify frequent genomic aberrations both in ESCC and esophageal dysplasia, and to discover important copy number-driving genes and microRNAs in ESCC. We carried out array-based comparative genomic hybridization (array CGH) on 59 ESCC resection samples and 16 dysplasia biopsy samples. Expression of genes at 11q13.3 was analyzed by real-time PCR and immunohistochemistry (IHC). Integrated analysis was performed to identify genes or microRNAs with copy number-expression correlations. Two group experiment, esophageal dysplasia vs. esophageal squamous cell carcinoma. Biological replicates: 16 dysplasias vs. 59 carcinomas
2013-04-29 | E-GEOD-46452 | biostudies-arrayexpress
Project description:Background & Aims: Esophageal squamous cell carcinoma (ESCC) is believed to arise from esophageal mucosa through accumulation of both genetic and epigenetic changes. DNA methylation is a critical epigenetic mechanism involved in key cellular processes and its deregulation has been linked to many human cancers, including ESCC. The aim of this study is to examine the global deregulation of methylation states in ESCC and identify potential early biomarkers. Conclusions: This is the first study to address methylation changes in ESCC in a large panel of genes. Methylome analysis is shown as a sensitive and powerful tool to identify molecular players in ESCC. These data should prove to be the reference for future studies identifying potential biomarkers and molecular targets of ESCC.
2011-11-23 | GSE26784 | GEO
Project description:Preoperative chemoradiotherapy (CRT) followed by surgery has been proved to improve esophageal squamous cell carcinoma (ESCC) patients’ survival in comparison with surgery alone. However, the outcomes of CRT are heterogeneous, and no clinical or pathological method could predict CRT response. We aim to identify mRNA markers for ESCC CRT-response prediction through gene expression analyses.
2014-08-01 | GSE45670 | GEO