Dataset Information

Identification of genes associated with histologic tumor grade of esophageal squamous cell carcinoma.

ABSTRACT: The present study aimed to identify the genes associated with the histologic tumor grade of patients with esophageal squamous cell carcinoma (ESCC) and to provide valuable information for the identification of potential diagnostic biomarkers in ESCC. Tumor samples of ESCC patients retrieved from The Cancer Genome Atlas were divided into Grade 1 (well-differentiated; G1), Grade 2 (moderately-differentiated; G2) and Grade 3 (poorly-differentiated; G3) groups in accordance with the clinical record of the tumor grade of ESCC patients. The genes associated with tumor grade were identified. The signaling pathways of identified genes were enriched from the Kyoto Encyclopedia of Genes and Genomes (KEGG). The diagnostic value of candidate genes was assessed by receiver operating characteristic analysis. We used the GSE23400 dataset generated from the Gene Expression Omnibus to examine the expression levels of candidate genes in ESCC tissues compared to matched mucosa tissues. In total, 440 genes positively correlated with tumor grade and 882 genes negatively correlated with tumor grade were identified. There were 310 differentially expressed genes (DEGs) between G1 and G2, 184 DEGs between G2 and G3, and 710 DEGs between G1 and G3. There were 1322 genes associated with tumor grade that were significantly enriched in pathways in cancer and the phospholipase D signaling pathway. Cyclin-dependent kinase inhibitor 1A, golgin A7 family member B and transforming growth factor B1-induced anti-apoptotic factor 1 (TIAF1) had potential diagnostic value for discriminating ESCC patients with G1 from those with G3. TIAF1 was significantly down-regulated in ESCC. The results of the present study comprise useful groundwork with respect to determining the tumorigenesis mechanism in ESCC and discovering potential diagnostic biomarkers for ESCC.

SUBMITTER: Xing J

PROVIDER: S-EPMC5586336 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of genes associated with histologic tumor grade of esophageal squamous cell carcinoma.

Xing Jiaqiang J Liu Cuicui C

FEBS open bio 20170728 9

The present study aimed to identify the genes associated with the histologic tumor grade of patients with esophageal squamous cell carcinoma (ESCC) and to provide valuable information for the identification of potential diagnostic biomarkers in ESCC. Tumor samples of ESCC patients retrieved from <i>The Cancer Genome Atlas</i> were divided into Grade 1 (well-differentiated; G1), Grade 2 (moderately-differentiated; G2) and Grade 3 (poorly-differentiated; G3) groups in accordance with the clinical ...[more]

PMID: 28904855

Similar Datasets

Project description:Background Esophageal cancer (EC) is a highly aggressive malignancy that is classified as esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). Infiltrating stromal/immune cells, a major component of the tumor immune microenvironment (TIME), have prognostic significance in various cancers. Methods In this study we investigated genes and immune factors in the tumor microenvironment (TME) of ESCC and EAC that can serve as prognostic biomarkers. Stromal and immune scores were calculated using the Estimation of Stromal and Immune Cells in Malignant Tumor Tissues Using Expression Data (ESTIMATE) algorithm based on gene expression profiles of patient-derived tumor tissues in The Cancer Genome Atlas database. The correlation between ESTIMATE scores and survival rates in EC were analyzed. A comparison of high and low stromal/immune score groups revealed multiple differentially expressed genes (DEGs) as candidate prognostic genes; their role in immune-related biological processes was evaluated by functional and protein-protein interaction (PPI) network analyses, and the genes were validated using Gene Expression Omnibus datasets. Additionally, 22 tumor-infiltrating immune cell (TIIC) subsets were analyzed using the CIBERSORT algorithm. Results Median stromal score was higher whereas immune score was lower in ESCC than in EAC (both P<0.01). Stromal score was lower in female as compared to male ESCC patients (P<0.05), and was significantly correlated with T stage (P<0.05). In EAC, median immune score was higher in female as compared to male patients (P<0.05) and was correlated with tumor-node-metastasis stage (P<0.05). The identified DEGs were mainly involved in lymphocyte (especially T-lymphocyte) activation and carbohydrate binding. Moreover, the levels of infiltrating resting-stage dendritic cells, CD8+ T cells, naïve B cells, activated mast cells, and resting memory CD4+ T cells were significantly correlated with EC prognosis (P<0.05). Conclusions The immune microenvironment of ESCC and EAC are quite different. We have found genes with prognostic value in multiple tumor databases.

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 of genes associated with histologic tumor grade of esophageal squamous cell carcinoma.

Publications

Identification of genes associated with histologic tumor grade of esophageal squamous cell carcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets