Differential gene expression profiling of oesophageal squamous cell carcinoma by DNA microarray and bioinformatics analysis

Landscape of expression profiles in esophageal carcinoma by The Cancer Genome Atlas data

In this study, we explored the gene and microRNA (miRNA) expressions profile of esophageal carcinoma. The expression data for messenger RNAs and miRNAs in normal and cancerous esophageal tissues were obtained from the Cancer Genome Atlas database and then the differentially expressed genes and miRNAs were identified. As a result, we identified 2962 genes and 45 miRNAs differentially expressed in esophageal carcinoma compared with normal esophageal tissues. Subsequently, the altered gene functions and signaling pathways were investigated using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, and these differentially expressed genes were significantly enriched in the cell cycle, cell migration, mitogen-activated protein kinase (MAPK) and toll-like receptor signaling pathway, and so on. Then the regulatory relationships between the differentially expressed miRNAs and genes were examined with Targetscan and Miranda, and the potential target sites of transcription factors (TFs) in the promoter regions of these miRNAs and genes were identified using the TRANSFAC database. Finally the TF-miRNA-gene network in esophageal cancer was established, summarizing the regulatory links among the TFs, differentially expressed miRNAs and differentially expressed genes. Factors such as core promoter-binding protein (CPBP), nuclear factor of activated T-cells 1 (NFAT-1), miR-30c-5p, were located in the central hub of this network, highlighting their vital roles in esophageal tumorigenesis. These findings may extend our understanding of the molecular mechanisms underlying esophageal carcinoma and promote new perspectives for prevention, diagnosis and treatment.

Prediction of long noncoding RNA functions with co-expression network in esophageal squamous cell carcinoma

Background

Long non-coding RNAs (lncRNAs) are pervasively transcribed in the genome. They have important regulatory functions in chromatin remodeling and gene expression. Dysregulated lncRNAs have been studied in cancers, but their role in esophageal squamous cell carcinoma (ESCC) remains largely unknown. We have conducted lncRNA expression screening and a genome-wide analysis of lncRNA and coding gene expression on primary tumor and adjacent normal tissue from four ESCC patients, tend to understand the functionality of lncRNAs in carcinogenesis of esopheagus in combination with experimental and bioinformatics approach.

Methods

LncRNA array was used for coding and non-coding RNA expression. R program and Bioconductor packages (limma and RedeR) were used for differential expression and co-expression network analysis, followed by independent confirmation and functional studies of inferred onco-lncRNA ESCCAL-1 using quantitative real time polymerase chain reaction, small interfering RNA-mediated knockdown, apoptosis and invasion assays in vitro.

Results

The global coding and lncRNA gene expression pattern is able to distinguish ESCC from adjacent normal tissue. The co-expression network from differentially expressed coding and lncRNA genes in ESCC was constructed, and the lncRNA function may be inferred from the co-expression network. LncRNA ESCCAL-1 is such an example as a predicted novel onco-lncRNA, and it is overexpressed in 65% of an independent ESCC patient cohort (n = 26). More over, knockdown of ESCCAL-1 expression increases esophageal cancer cell apoptosis and reduces the invasion in vitro.

Conclusion

Our study uncovered the landscape of ESCC-associated lncRNAs. The systematic analysis of coding and lncRNAs co-expression network increases our understanding of lncRNAs in biological network. ESCCAL-1 is a novel putative onco-lncRNA in esophageal cancer development.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-015-1179-z) contains supplementary material, which is available to authorized users.

Identification of biomarkers for esophageal squamous cell carcinoma using feature selection and decision tree methods

Esophageal squamous cell cancer (ESCC) is one of the most common fatal human cancers. The identification of biomarkers for early detection could be a promising strategy to decrease mortality. Previous studies utilized microarray techniques to identify more than one hundred genes; however, it is desirable to identify a small set of biomarkers for clinical use. This study proposes a sequential forward feature selection algorithm to design decision tree models for discriminating ESCC from normal tissues. Two potential biomarkers of RUVBL1 and CNIH were identified and validated based on two public available microarray datasets. To test the discrimination ability of the two biomarkers, 17 pairs of expression profiles of ESCC and normal tissues from Taiwanese male patients were measured by using microarray techniques. The classification accuracies of the two biomarkers in all three datasets were higher than 90%. Interpretable decision tree models were constructed to analyze expression patterns of the two biomarkers. RUVBL1 was consistently overexpressed in all three datasets, although we found inconsistent CNIH expression possibly affected by the diverse major risk factors for ESCC across different areas.

Integrated analysis of long noncoding RNA and coding RNA expression in esophageal squamous cell carcinoma

Tumorigenesis is a complex dynamic biological process that includes multiple steps of genetic and epigenetic alterations, aberrant expression of noncoding RNA, and changes in the expression profiles of coding genes. We call the collection of those perturbations in genome space the “cancer initiatome.” Long noncoding RNAs (lncRNAs) are pervasively transcribed in the genome and they have key regulatory functions in chromatin remodeling and gene expression. Spatiotemporal variation in the expression of lncRNAs has been observed in development and disease states, including cancer. A few dysregulated lncRNAs have been studied in cancers, but the role of lncRNAs in the cancer initiatome remains largely unknown, especially in esophageal squamous cell carcinoma (ESCC). We conducted a genome-wide screen of the expression of lncRNAs and coding RNAs from ESCC and matched adjacent nonneoplastic normal tissues. We identified differentially expressed lncRNAs and coding RNAs in ESCC relative to their matched normal tissue counterparts and validated the result using polymerase chain reaction analysis. Furthermore, we identified differentially expressed lncRNAs that are co-located and co-expressed with differentially expressed coding RNAs in ESCC and the results point to a potential interaction between lncRNAs and neighboring coding genes that affect ether lipid metabolism, and the interaction may contribute to the development of ESCC. These data provide compelling evidence for a potential novel genomic biomarker of esophageal squamous cell cancer.