Dataset Information

Identification of potential biomarkers in Barrett's esophagus derived esophageal adenocarcinoma.

ABSTRACT: Almost 50% of esophageal adenocarcinoma (EAC) patients progressed from Barrett's esophagus (BE). EAC is often diagnosed at late stages and is related to dismal prognosis. However, there are still no effective methods for stratification and therapy in BE and EAC. Two public datasets (GSE26886 and GSE37200) were analyzed to identify differentially expressed genes (DEGs) between BE and EAC. Then, a series of bioinformatics analyses were performed to explore potential biomarkers associated with BE-EAC. 27 up- and 104 down-regulated genes were observed between GSE26886 and GSE37200. The GO and KEGG enrichment analysis indicated that the DEGs were highly involved in tumorigenesis. Subsequently, Weighted Gene Co-Expression Network Analysis (WGCNA) were performed to explore the potential genes related to BE-EAC, which were validated in The Cancer Genome Atlas (TCGA) database, and 5 up-regulated genes (MYO1A, ACE2, COL1A1, LGALS4, and ADRA2A) and 3 down-regulated genes (AADAC, RAB27A, and P2RY14) were found in EAC. Meanwhile, ADRA2A and AADAC could contribute to EAC pathogenesis and progression. MYO1A, ACE2, COL1A1, LGALS4, ADRA2A, AADAC, RAB27A, and P2RY14 could be potential novel diagnostic and prognostic biomarkers in BE-EAC.

SUBMITTER: Yi N

PROVIDER: S-EPMC9910260 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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Identification of potential biomarkers in Barrett's esophagus derived esophageal adenocarcinoma.

Yi Nan N Zhao Hailiang H He Juan J Xie Xike X Liang Liexin L Zuo Guowen G Xiong Mingyue M Liang Yunxiao Y Yi Tingzhuang T

Scientific reports 20230209 1

Almost 50% of esophageal adenocarcinoma (EAC) patients progressed from Barrett's esophagus (BE). EAC is often diagnosed at late stages and is related to dismal prognosis. However, there are still no effective methods for stratification and therapy in BE and EAC. Two public datasets (GSE26886 and GSE37200) were analyzed to identify differentially expressed genes (DEGs) between BE and EAC. Then, a series of bioinformatics analyses were performed to explore potential biomarkers associated with BE-E ...[more]

PMID: 36759514

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Project description:BACKGROUND:Esophageal adenocarcinoma (EAC) is an aggressive disease with high mortality and an overall 5-year survival rate of less than 20%. Barrett's esophagus (BE) is the only known precursor of EAC, and patients with BE have a persistent and excessive risk of EAC over time. Individuals with BE are up to 30-125 times more likely to develop EAC than the general population. Thus, early detection of EAC and BE could significantly improve the 5-year survival rate of EAC. Due to the limitations of endoscopic surveillance and the lack of clinical risk stratification strategies, molecular biomarkers should be considered and thoroughly investigated. AIM:To explore the transcriptome changes in the progression from normal esophagus (NE) to BE and EAC. METHODS:Two datasets from the Gene Expression Omnibus (GEO) in NCBI Database (https://www.ncbi.nlm.nih.gov/geo/) were retrieved and used as a training and a test dataset separately, since NE, BE, and EAC samples were included and the sample sizes were adequate. This study identified differentially expressed genes (DEGs) using the R/Bioconductor project and constructed trans-regulatory networks based on the Transcriptional Regulatory Element Database and Cytoscape software. Enrichment of Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) terms was identified using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) Bioinformatics Resources. The diagnostic potential of certain DEGs was assessed in both datasets. RESULTS:In the GSE1420 dataset, the number of up-regulated DEGs was larger than that of down-regulated DEGs when comparing EAC vs NE and BE vs NE. Among these DEGs, five differentially expressed transcription factors (DETFs) displayed the same trend in expression across all the comparison groups. Of these five DETFs, E2F3, FOXA2, and HOXB7 were up-regulated, while PAX9 and TFAP2C were down-regulated. Additionally, the majority of the DEGs in trans-regulatory networks were up-regulated. The intersection of these potential DEGs displayed the same direction of changes in expression when comparing the DEGs in the GSE26886 dataset to the DEGs in trans-regulatory networks above. The receiver operating characteristic curve analysis was performed for both datasets and found that TIMP1 and COL1A1 could discriminate EAC from NE tissue, while REG1A, MMP1, and CA2 could distinguish BE from NE tissue. DAVID annotation indicated that COL1A1 and MMP1 could be potent biomarkers for EAC and BE, respectively, since they participate in the majority of the enriched KEGG and GO terms that are important for inflammation and cancer. CONCLUSION:After the construction and analyses of the trans-regulatory networks in EAC and BE, the results indicate that COL1A1 and MMP1 could be potential biomarkers for EAC and BE, respectively.

Project description:BackgroundRecent studies have identified age-related changes in DNA methylation patterns in normal and cancer tissues in a process that is called epigenetic drift. However, the evolving patterns, functional consequences, and dynamics of epigenetic drift during carcinogenesis remain largely unexplored. Here we analyze the evolution of epigenetic drift patterns during progression from normal squamous esophagus tissue to Barrett's esophagus (BE) to esophageal adenocarcinoma (EAC) using 173 tissue samples from 100 (nonfamilial) BE patients, along with publically available datasets including The Cancer Genome Atlas (TCGA).ResultsOur analysis reveals extensive methylomic drift between normal squamous esophagus and BE tissues in nonprogressed BE patients, with differential drift affecting 4024 (24%) of 16,984 normally hypomethylated cytosine-guanine dinucleotides (CpGs) occurring in CpG islands. The majority (63%) of islands that include drift CpGs are associated with gene promoter regions. Island CpGs that drift have stronger pairwise correlations than static islands, reflecting collective drift consistent with processive DNA methylation maintenance. Individual BE tissues are extremely heterogeneous in their distribution of methylomic drift and encompass unimodal low-drift to bimodal high-drift patterns, reflective of differences in BE tissue age. Further analysis of longitudinally collected biopsy samples from 20 BE patients confirm the time-dependent evolution of these drift patterns. Drift patterns in EAC are similar to those in BE, but frequently exhibit enhanced bimodality and advanced mode drift. To better understand the observed drift patterns, we developed a multicellular stochastic model at the CpG island level. Importantly, we find that nonlinear feedback in the model between mean island methylation and CpG methylation rates is able to explain the widely heterogeneous collective drift patterns. Using matched gene expression and DNA methylation data in EAC from TCGA and other publically available data, we also find that advanced methylomic drift is correlated with significant transcriptional repression of ~ 200 genes in important regulatory and developmental pathways, including several checkpoint and tumor suppressor-like genes.ConclusionsTaken together, our findings suggest that epigenetic drift evolution acts to significantly reduce the expression of developmental genes that may alter tissue characteristics and improve functional adaptation during BE to EAC progression.

Dataset Information

Identification of potential biomarkers in Barrett's esophagus derived esophageal adenocarcinoma.

Publications

Identification of potential biomarkers in Barrett's esophagus derived esophageal adenocarcinoma.

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