Dataset Information

Identification and Characterization of Copy Number-Associated Driver Genes in Esophageal Squamous Cell Carcinoma.

ABSTRACT: Background:Esophageal squamous cell carcinoma (ESCC) is a leading malignancy with both high incidence and mortality worldwide. However, the molecular mechanisms of the poor prognosis in ESCC are still unclear. Methods:We conducted differential expression analysis between ESCC and normal tissues and between ESCC samples with and without CNAs in a given gene. Overrepresentation enrichment and gene set enrichment analyses were used to identify the oncogenic pathways and abnormal transcription factors (TFs). The survival analysis was employed to identify the genes associated with overall survival. Results:In this study, we aimed to identify and interpret the driver genes triggered by the copy number alterations (CNAs), including CCND1, TEAD4, EIF4EBP1, EGFR, FGFR3, and FZD6. Furthermore, we identified oncogenic pathways, including RTK-RAS, WNT, PI3K, Hippo, and cell cycle, and key TFs including TEAD4, a transcription factor in the Hippo signaling pathway, and LEF1 in the WNT signaling pathway. Furthermore, we observed that upregulations of FGFR3 and EIF4EBP1 were significantly associated with shorter overall survival in ESCC. Conclusion:In conclusion, the driver genes triggered by CNAs not only exhibited critical functionality but also were clinically relevant in ESCC, which greatly improved our understanding of the molecular mechanisms in ESCC.

SUBMITTER: Jiang K

PROVIDER: S-EPMC7463369 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Identification and Characterization of Copy Number-Associated Driver Genes in Esophageal Squamous Cell Carcinoma.

Jiang Kexin K He Yijiang Y Zhang Xu X

BioMed research international 20200822

<h4>Background</h4>Esophageal squamous cell carcinoma (ESCC) is a leading malignancy with both high incidence and mortality worldwide. However, the molecular mechanisms of the poor prognosis in ESCC are still unclear.<h4>Methods</h4>We conducted differential expression analysis between ESCC and normal tissues and between ESCC samples with and without CNAs in a given gene. Overrepresentation enrichment and gene set enrichment analyses were used to identify the oncogenic pathways and abnormal tran ...[more]

PMID: 32908901

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Project description:Background: Esophageal cancer (EC) is one of the deadliest cancers in the world. However, the mechanism that drives the evolution of EC is still unclear. On this basis, we identified the key genes and molecular pathways that may be related to the progression of esophageal adenocarcinoma and squamous cell carcinoma to find potential markers or therapeutic targets. Methods: GSE26886 were obtained from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) among normal samples, EA, and squamous cell carcinoma were determined using R software. Then, potential functions of DEGs were determined using the Database for Annotation, Visualization and Integrated Discovery (DAVID). The STRING software was used to identify the most important modules in the protein-protein interaction (PPI) network. The expression levels of hub genes were confirmed using UALCAN database. Kaplan-Meier plotters were used to confirm the correlation between hub genes and outcomes in EC. Results: In this study, we identified 1,098 genes induced in esophageal adenocarcinoma (EA) and esophageal squamous cell carcinoma (ESCC), and 669 genes were reduced in EA and ESCC, suggesting that these genes may play an important role in the occurrence and development of EC tumors. Bioinformatics analysis showed that these genes were involved in cell cycle regulation and p53 and phosphoinositide 3-kinase (PI3K)/Akt signaling pathway. In addition, we identified 147 induced genes and 130 reduced genes differentially expressed in EA and ESCC. The expression of ESCC in the EA group was different from that in the control group. By PPI network analysis, we identified 10 hub genes, including GNAQ, RGS5, MAPK1, ATP1B1, HADHA, HSDL2, SLC25A20, ACOX1, SCP2, and NLN. TCGA validation showed that these genes were present in the dysfunctional samples between EC and normal samples and between EA and ESCC. Kaplan-Meier analysis showed that MAPK1, ACOX1, SCP2, and NLN were associated with overall survival in patients with ESCC and EA. Conclusions: In this study, we identified a series of DEGs between EC and normal samples and between EA and ESCC samples. We also identified 10 key genes involved in the EC process. We believe that this study may provide a new biomarker for the prognosis of EA and ESCC.

Project description:To uncover the genes associated with the development of esophageal squamous cell carcinoma (ESCC), an ESCC microarray dataset was used to identify genes differentially expressed between ESCC and normal control tissues. The dataset GSE17351 was downloaded from the Gene Expression Omnibus, containing 5 tumor esophageal mucosa samples and 5 adjacent normal esophageal mucosa samples from 5 male patients with ESCC. The differentially expressed genes (DEGs) were identified using the Linear Models for Microarray Data R package. Then, a co-expression network was constructed using the Weighted Correlation Network Analysis (WGCNA) package, and co-expression network modules were obtained with a hierarchical clustering algorithm. Additionally, functional enrichment analyses for DEGs in the top 2 modules with the highest significance were respectively conducted using the WGCNA package and the cluster Profiler package. In total, 487 upregulated and 468 downregulated DEGs were identified. A total of 24 modules were obtained from the co-expression network, and the top 2 modules with the highest significance, designated as 'blue4' and 'magenta', were further analyzed. In the module blue4, DEGs were significantly enriched in a number of Gene Ontology terms, including 'spindle organization' [e.g., ubiquitin conjugating enzyme E2 C (UBE2C) and SAC3 domain containing 1] and 'cell cycle process' [e.g., UBE2C, minichromosome maintenance complex component 6 (MCM6) and cell division cycle 20 (CDC20)]. Furthermore, a number of DEGs (e.g., UBE2C, CDC20 and MCM6) were enriched in the 'cell cycle' and 'ubiquitin mediated proteolysis' pathways. In the module 'magenta', a number of DEGs [e.g., transferrin receptor (TFRC) and TEA domain transcription factor 4 (TEAD4)] were enriched in the primary metabolic process and intracellular membrane-bounded organelle. Additionally, 308 upregulated genes and 215 downregulated genes were differentially expressed in the same pattern in another dataset, GSE20347, including UBE2C, CDC20, MCM6, TFRC, TEAD4, protein phosphatase 1 regulatory subunit 3C and MAL, T-cell differentiation protein. These DEGs may function in the development of ESCC.

Dataset Information

Identification and Characterization of Copy Number-Associated Driver Genes in Esophageal Squamous Cell Carcinoma.

Publications

Identification and Characterization of Copy Number-Associated Driver Genes in Esophageal Squamous Cell Carcinoma.

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