Methylome and transcriptome of EAC
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ABSTRACT:
PROVIDER: PRJNA295227 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:genome-wide methylation profile of 250 samples including 125 EAC, 19 Barrett’s, 64 normal adjacent squamous and 21 normal stomach. Transcriptome data was performed for 70 samples with methylation profile (48 EAC, 4 Barrett’s and 18 normal adjacent squamous). This is the first study to use methylome, transcriptome and ENCODE data to characterize the regulatory role of methylation in EAC.
2016-05-01 | GSE72873 | GEO
Project description:genome-wide methylation profile of 250 samples including 125 EAC, 19 Barrett’s, 64 normal adjacent squamous and 21 normal stomach. Transcriptome data was performed for 70 samples with methylation profile (48 EAC, 4 Barrett’s and 18 normal adjacent squamous). This is the first study to use methylome, transcriptome and ENCODE data to characterize the regulatory role of methylation in EAC.
2016-05-01 | GSE72872 | GEO
Project description:m5C methylome, transcriptome and proteome of sysnechocystis
| PXD055431 |
Project description:Despite continual efforts to rationalize a prognostic stratification of patients with esophageal adenocarcinoma (EAC) before treatment, current staging system only shows limited success owing to the lack of molecular and genetic markers that reflect prognostic features of the tumor. To develop molecular predictors of prognosis, we used systems-level characterization of tumor transcriptome. Using DNA microarray, genome-wide gene expression profiling was performed on 75 biopsy samples from patients with untreated EAC. Various statistical and informatical methods were applied to gene expression data to identify potential biomarkers associated with prognosis. Potential marker genes were validated in an independent cohort using quantitiative RT-PCR to measure gene expression. Distinct subgroups of EAC were uncovered by systems-level characterization of tumor transcriptome. We also identified a six-gene expression signature that could be used to predict overall survival (OS) of EAC patients. In particular, expression of SPARC and SPP1 was a strong independent predictor of OS, and a combined gene expression signature with these two genes was associated with prognosis (P < 0.024), even when all relevant pathological variables were considered together in multivariate Cox hazard regression analysis. Our findings suggest that molecular features reflected in gene expression signatures may dictate the prognosis of EAC patients, and these gene expression signatures can be used to predict the likelihood of prognosis at the time of diagnosis and before treatment.
2011-01-04 | GSE13898 | GEO
Project description:Classically, there are two types of endometrial cancer, endometrioid adenocarcinoma (EAC), or Type I; and uterine papillary serous carcinoma (UPSC), or Type II. These two types of cancers exhibit distinct DNA methylation levels in promoters of many genes. In EAC, many tumor suppressor genes were silenced due to DNA hypermethylation at their promoter region. However, promoters of many of these genes remained unmethylated in UPSC. Here, we described complete DNA methylome maps of endometrioid adenocarcinoma, uterine papillary serous carcinoma, and normal endometrium, by applying a combined strategy of methylated DNA immunoprecipitation sequencing (MeDIP-seq) and methylation-sensitive restriction enzyme sequencing (MRE-seq). We took a complementary and orthogonal approach to identify DNA methylation changes unique to the two endometrial cancer subtypes in an unbiased fashion. We generated complete DNA methylome maps for endometrioid adenocarcinoma (EAC, three samples), uterine papillary serous carcinomas (UPSC, three samples), and normal endometrium (pooled samples) by integrating data from methylated DNA immunoprecipitation sequencing (MeDIP-seq) and methylation-sensitive restriction enzyme sequencing (MRE-seq).
2014-10-12 | E-GEOD-51565 | biostudies-arrayexpress
Project description:Despite continual efforts to rationalize a prognostic stratification of patients with esophageal adenocarcinoma (EAC) before treatment, current staging system only shows limited success owing to the lack of molecular and genetic markers that reflect prognostic features of the tumor. To develop molecular predictors of prognosis, we used systems-level characterization of tumor transcriptome. Using DNA microarray, genome-wide gene expression profiling was performed on 75 biopsy samples from patients with untreated EAC. Various statistical and informatical methods were applied to gene expression data to identify potential biomarkers associated with prognosis. Potential marker genes were validated in an independent cohort using quantitiative RT-PCR to measure gene expression. Distinct subgroups of EAC were uncovered by systems-level characterization of tumor transcriptome. We also identified a six-gene expression signature that could be used to predict overall survival (OS) of EAC patients. In particular, expression of SPARC and SPP1 was a strong independent predictor of OS, and a combined gene expression signature with these two genes was associated with prognosis (P < 0.024), even when all relevant pathological variables were considered together in multivariate Cox hazard regression analysis. Our findings suggest that molecular features reflected in gene expression signatures may dictate the prognosis of EAC patients, and these gene expression signatures can be used to predict the likelihood of prognosis at the time of diagnosis and before treatment. 64 primary esophageal adenocarcinoma, 15 Barrett's esophagus and 28 surrounding normal fresh frozen tissues were used for microarray. All the tissues were obtained after curative resection after pathologic confirm at UT M.D. Anderson Cancer Center (MDACC). Microarray experiment and data analysis were done in the Dept. of systems biology at MDACC DNA microarray (Illumina human V2)
2011-01-04 | E-GEOD-13898 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the SubSeries listed below.
2016-05-01 | GSE72874 | GEO
Project description:Gastroesophageal reflux disease (GERD) is the predominant risk factor for the development of Barrett’s esophagus and esophageal adenocarcinoma (EAC). However, the molecular mechanisms driving responses to chronic reflux conditions in EAC remain poorly defined. This study investigates the genome-wide transcriptional reprogramming and molecular stress responses mediated by apurinic/apyrimidinic endonuclease 1 (APE1) in EAC cells (OE33) surviving chronic, reflux-induced stress. By pairing a 15-day repeated acidified bile salt (rABS) exposure model with subsequent APE1 genetic silencing, this dataset defines the global differential gene expression profiles, altered signaling pathways, and transcriptional networks that depend on APE1 for acquired stress tolerance during sustained reflux insults.
2026-08-11 | GSE342970 | GEO
Project description:Methylome and transcriptome of EAC (methylation)
| PRJNA295229 | ENA