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Global gene expression profiling and validation in esophageal squamous cell carcinoma and its association with clinical phenotypes.

ABSTRACT: PURPOSE:Esophageal squamous cell carcinoma (ESCC) is an aggressive tumor with poor prognosis. Understanding molecular changes in ESCC will enable identification of molecular subtypes and provide potential targets for early detection and therapy. EXPERIMENTAL DESIGN:We followed up a previous array study with additional discovery and confirmatory studies in new ESCC cases by using alternative methods. We profiled global gene expression for discovery and confirmation, and validated selected dysregulated genes with additional RNA and protein studies. RESULTS:A total of 159 genes showed differences with extreme statistical significance (P < E-15) and 2-fold differences or more in magnitude (tumor/normal RNA expression ratio, N = 53 cases), including 116 upregulated and 43 downregulated genes. Of 41 genes dysregulated in our prior array study, all but one showed the same fold change directional pattern in new array studies, including 29 with 2-fold changes or more. Alternative RNA expression methods validated array results: more than two thirds of 51 new cases examined by real-time PCR (RT-PCR) showed 2-fold differences or more for all seven genes assessed. Immunohistochemical protein expression results in 275 cases which were concordant with RNA for five of six genes. CONCLUSION:We identified an expanded panel of genes dysregulated in ESCC and confirmed previously identified differentially expressed genes. Microarray-based gene expression results were confirmed by RT-PCR and protein expression studies. These dysregulated genes will facilitate molecular categorization of tumor subtypes and identification of their risk factors, and serve as potential targets for early detection, outcome prediction, and therapy.

SUBMITTER: Su H

PROVIDER: S-EPMC3086948 | biostudies-literature | 2011 May

REPOSITORIES: biostudies-literature

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Global gene expression profiling and validation in esophageal squamous cell carcinoma and its association with clinical phenotypes.

Su Hua H Hu Nan N Yang Howard H HH Wang Chaoyu C Takikita Mikiko M Wang Quan-Hong QH Giffen Carol C Clifford Robert R Hewitt Stephen M SM Shou Jian-Zhong JZ Goldstein Alisa M AM Lee Maxwell P MP Taylor Philip R PR

Clinical cancer research : an official journal of the American Association for Cancer Research 20110308 9

<h4>Purpose</h4>Esophageal squamous cell carcinoma (ESCC) is an aggressive tumor with poor prognosis. Understanding molecular changes in ESCC will enable identification of molecular subtypes and provide potential targets for early detection and therapy.<h4>Experimental design</h4>We followed up a previous array study with additional discovery and confirmatory studies in new ESCC cases by using alternative methods. We profiled global gene expression for discovery and confirmation, and validated s ...[more]

PMID: 21385931

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Project description:ImportancePatients with late-stage esophageal squamous cell carcinoma (ESCC) have a poor prognosis. Noninvasive screening tests using serum microRNAs (miRNAs) to accurately detect early-stage ESCC are needed to improve mortality.ObjectiveTo establish a model using serum miRNAs to distinguish patients with ESCC from noncancer controls.Design, setting, and participantsIn this case-control study, serum miRNA expression profiles of patients with ESCC (n = 566) and control patients without cancer (n = 4965) were retrospectively analyzed to establish a diagnostic model, which was tested in a training set and confirmed in a validation set. Patients histologically diagnosed as having ESCC who did not receive prior therapy or have a past or concurrent cancer other than ESCC were enrolled from the National Cancer Center Hospital in Tokyo, Japan. Between October 2010 and November 2015, control samples were collected from the National Cancer Center Biobank, the Biobank of the National Center for Geriatrics and Gerontology, and the general population undergoing routine health examination. Data analysis was performed between August 2015 and October 2018. Serum samples were randomly divided into discovery and validation sets.Main outcomes and measuresThe expression of 2565 miRNAs was assessed in each sample. The discriminant model (named the EC index) was evaluated in the training set using Fisher linear discriminant analysis with a greedy algorithm. Receiver operating characteristic curve analysis evaluated the diagnostic ability of the model in the validation set.ResultsIn the training set, 283 patients with esophageal cancer (median age, 67 years [range, 37-90 years]; 83.4% male) were compared with 283 control patients (median age, 54 years [range, 22-100 years]; 43.1% male), and the EC index was constructed using 6 miRNAs (miR-8073, miR-6820-5p, miR-6794-5p, miR-3196, miR-744-5p, and miR-6799-5p). The area under the receiver operating characteristic curve was 1.00, with sensitivity of 1.00 and specificity of 0.98. The validation set included 283 patients (median age, 66 years [range, 42-87 years]; 83.0% male) and 4682 control patients (median age, 68 years [range, 20-98 years]; 44.7% male), and the area under the receiver operating characteristic curve for the EC index was 1.00, with sensitivity of 0.96 and specificity of 0.98.Conclusions and relevanceWhat appears to be novel serum miRNA discriminant model was developed for the diagnosis of ESCC. A multicenter prospective study is ongoing to confirm the present observations.

Project description:BackgroundEsophageal squamous cell carcinoma (ESCC) has a poor prognosis and is one of the deadliest gastrointestinal malignancies. Despite numerous transcriptomics studies to understand its molecular basis, the impact of population-specific differences on this disease remains unexplored.AimsThis study aimed to investigate the population-specific differences in gene expression patterns among ESCC samples obtained from six distinct global populations, identify differentially expressed genes (DEGs) and their associated pathways, and identify potential biomarkers for ESCC diagnosis and prognosis. In addition, this study deciphers population specific microbial and chemical risk factors in ESCC.MethodsWe compared the gene expression patterns of ESCC samples from six different global populations by analyzing microarray datasets. To identify DEGs, we conducted stringent quality control and employed linear modeling. We cross-compared the resulting DEG lists of each populations along with ESCC ATLAS to identify known and novel DEGs. We performed a survival analysis using The Cancer Genome Atlas Program (TCGA) data to identify potential biomarkers for ESCC diagnosis and prognosis among the novel DEGs. Finally, we performed comparative functional enrichment and toxicogenomic analysis.ResultsHere we report 19 genes with distinct expression patterns among populations, indicating population-specific variations in ESCC. Additionally, we discovered 166 novel DEGs, such as ENDOU, SLCO1B3, KCNS3, IFI35, among others. The survival analysis identified three novel genes (CHRM3, CREG2, H2AC6) critical for ESCC survival. Notably, our findings showed that ECM-related gene ontology terms and pathways were significantly enriched among the DEGs in ESCC. We also found population-specific variations in immune response and microbial infection-related pathways which included genes enriched for HPV, Ameobiosis, Leishmaniosis, and Human Cytomegaloviruses. Our toxicogenomic analysis identified tobacco smoking as the primary risk factor and cisplatin as the main drug chemical interacting with the maximum number of DEGs across populations.ConclusionThis study provides new insights into population-specific differences in gene expression patterns and their associated pathways in ESCC. Our findings suggest that changes in extracellular matrix (ECM) organization may be crucial to the development and progression of this cancer, and that environmental and genetic factors play important roles in the disease. The novel DEGs identified may serve as potential biomarkers for diagnosis, prognosis and treatment.

Project description:BackgroundEsophageal squamous cell carcinoma (ESCC) is a subtype of esophageal cancer with high incidence and mortality. Due to the poor 5-year survival rates of patients with ESCC, exploring novel diagnostic markers for early ESCC is emergent. Collagen, the abundant constituent of extracellular matrix, plays a critical role in tumor growth and epithelial-mesenchymal transition. However, the clinical significance of collagen genes in ESCC has been rarely studied. In this work, we systematically analyzed the gene expression of whole collagen family in ESCC, aiming to search for ideal biomarkers.MethodsClinical data and gene expression profiles of ESCC patients were collected from The Cancer Genome Atlas and the gene expression omnibus databases. Bioinformatics methods, including differential expression analysis, survival analysis, gene sets enrichment analysis (GSEA) and co-expression network analysis, were performed to investigate the correlation between the expression patterns of 44 collagen family genes and the development of ESCC.ResultsA total of 22 genes of collagen family were identified as differentially expressed genes in both the two datasets. Among them, COL1A1, COL10A1 and COL11A1 were particularly up-regulated in ESCC tissues compared to normal controls, while COL4A4, COL6A5 and COL14A1 were notably down-regulated. Besides, patients with low COL6A5 expression or high COL18A1 expression showed poor survival. In addition, a 7-gene prediction model was established based on collagen gene expression to predict patient survival, which had better predictive accuracy than the tumor-node-metastasis staging based model. Finally, GSEA results suggested that collagen genes might be tightly associated with PI3K/Akt/mTOR pathway, p53 pathway, apoptosis, cell cycle, etc.ConclusionSeveral collagen genes could be potential diagnostic and prognostic biomarkers for ESCC. Moreover, a novel 7-gene prediction model is probably useful for predicting survival outcomes of ESCC patients. These findings may facilitate early detection of ESCC and help improves prognosis of the patients.

Dataset Information

Global gene expression profiling and validation in esophageal squamous cell carcinoma and its association with clinical phenotypes.

Publications

Global gene expression profiling and validation in esophageal squamous cell carcinoma and its association with clinical phenotypes.

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