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Multivariate gene expression-based survival predictor model in esophageal adenocarcinoma.

ABSTRACT: BACKGROUND:Despite the recent development of molecular-targeted treatment and immunotherapy, survival of patients with esophageal adenocarcinoma (EAC) with poor prognosis is still poor due to lack of an effective biomarker. In this study, we aimed to explore the ceRNA and construct a multivariate gene expression predictor model using data from The Cancer Genome Atlas (TCGA) to predict the prognosis of EAC patients. METHODS:We conducted differential expression analysis using mRNA, miRNA and lncRNA transciptome data from EAC and normal patients as well as corresponding clinical information from TCGA database, and gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of those unique differentially expressed mRNAs using the Integrate Discovery Database (DAVID) database. We then constructed the lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network of EAC and used Cox proportional hazard analysis to generate a multivariate gene expression predictor model. We finally performed survival analysis to determine the effect of differentially expressed mRNA on patients' overall survival and discover the hub gene. RESULTS:We identified a total of 488 lncRNAs, 33 miRNAs, and 1207 mRNAs with differentially expressed profiles. Cox proportional hazard analysis and survival analysis using the ceRNA network revealed four genes (IL-11, PDGFD, NPTX1, ITPR1) as potential biomarkers of EAC prognosis in our predictor model, and IL-11 was identified as an independent prognostic factor. CONCLUSIONS:In conclusion, we identified differences in the ceRNA regulatory networks and constructed a four-gene expression-based survival predictor model, which could be referential for future clinical research.

SUBMITTER: Zhao M

PROVIDER: S-EPMC7529573 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Multivariate gene expression-based survival predictor model in esophageal adenocarcinoma.

Zhao Maoyuan M Wang Jingsong J Yuan Meng M Ma Zeliang Z Bao Yongxin Y Hui Zhouguang Z

Thoracic cancer 20200901 10

<h4>Background</h4>Despite the recent development of molecular-targeted treatment and immunotherapy, survival of patients with esophageal adenocarcinoma (EAC) with poor prognosis is still poor due to lack of an effective biomarker. In this study, we aimed to explore the ceRNA and construct a multivariate gene expression predictor model using data from The Cancer Genome Atlas (TCGA) to predict the prognosis of EAC patients.<h4>Methods</h4>We conducted differential expression analysis using mRNA, ...[more]

PMID: 32869505

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Project description:Esophageal adenocarcinoma (EAC) has become the dominant type of esophageal cancer in United States. The 5-year survival rate of EAC is below 20% and most patients present with locally advanced or widespread metastatic disease, where current treatment is largely ineffective. Therefore, new therapeutic approaches are urgently needed. Improvement of EAC patient outcome requires well-characterized animal models in which to evaluate novel therapeutics. In this study we aimed to establish a peritoneal dissemination xenograft mouse model of EAC that would support survival outcome analyses. To find the best candidate cell line from 7 human EAC cell lines of different origin named ESO26, OE33, ESO51, SK-GT-2, OE19, OACM5.1C and Flo-1 were injected intraperitoneally/subcutaneously into SCID mice. The peritoneal/xenograft tumor formation and mouse survival were compared among different groups. All cell lines injected subcutaneously formed tumors within 3 months at variable rates. All cell lines except OACM5.1C formed intraperitoneal tumors within 3 months at variable rates. Median animal survival with peritoneal dissemination was 108 days for ESO26 cells (5X106), 65 days for OE33 cells (5X106), 88 days for ESO51 cells (5X106), 76 days for SK-GT-2 cells (5X106), 55 days for OE19 cells (5X106), 45 days for OE19 cells (10X106) and 82 days for Flo-1 cells (5X106). Interestingly, only in the OE19 model all mice (7/7 for 5X106 and 5/5 for10X106) developed bloody ascites with liver metastasis after intraperitoneal injection. The median survival time of these animals was the shortest (45 days for 10X106 cells). In addition, median survival was significantly increased after paclitaxel treatment compared with the control group (57 days versus 45 days, p = 0.0034) along with a significant decrease of the relative subcutaneous tumor volume (p = 0.00011). Thus peritoneal dissemination mouse xenograft model for survival outcome assessment after intraperitoneal injection of OE19 cells will be very useful for the evaluation of cancer therapeutics.

Dataset Information

Multivariate gene expression-based survival predictor model in esophageal adenocarcinoma.

Publications

Multivariate gene expression-based survival predictor model in esophageal adenocarcinoma.

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