Dataset Information

Detection of differentially expressed genes and association with clinicopathological features in laryngeal squamous cell carcinoma.

ABSTRACT: Head and neck cancer is a significant health problem worldwide. Early detection and prediction of prognosis will improve patient survival and quality of life. The aim of this study was to identify genes differentially expressed between laryngeal cancer and the corresponding normal tissues as potential biomarkers. A total of 36 patients with laryngeal squamous cell carcinoma were recruited. Four of these cases were randomly selected for cDNA microarray analysis of the entire genome. Using semi-quantitative RT-PCR and western blot analysis, the differential expression of genes and their protein products, respectively, between laryngeal cancer tissues and corresponding adjacent normal tissues was verified in the remaining 32 cases. The expression levels of these genes and proteins were investigated for associations with clinicopathological parameters taken from patient data. The cDNA microarray analysis identified 349 differentially expressed genes between tumor and normal tissues, 112 of which were upregulated and 237 were downregulated in tumors. Seven genes and their protein products were then selected for validation using RT-PCR and western blot analysis, respectively. The data demonstrated that the expression of SENP1, CD109, CKS2, LAMA3, ITGAV and ITGB8 was increased, while LAMA2 was downregulated in laryngeal cancer compared with the corresponding normal tissues. Associations between the expression of these genes and clinicopathological data from the patients were also established, including age, tumor classification, stage, differentiation and lymph node metastasis. Our current study provides the first evidence that these seven genes may be differentially expressed in laryngeal squamous cell carcinoma and also associated with clinicopathological data. Future study is required to further confirm whether detection of their expression can be used as biomarkers for prediction of patient survival or potential treatment targets.

SUBMITTER: Ni RS

PROVIDER: S-EPMC3506781 | biostudies-literature | 2012 Dec

REPOSITORIES: biostudies-literature

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Detection of differentially expressed genes and association with clinicopathological features in laryngeal squamous cell carcinoma.

Ni Rong Sheng RS Shen Xiaohui X Qian Xiaoyun X Yu Chenjie C Wu Haiyan H Gao Xia X

Oncology letters 20120918 6

Head and neck cancer is a significant health problem worldwide. Early detection and prediction of prognosis will improve patient survival and quality of life. The aim of this study was to identify genes differentially expressed between laryngeal cancer and the corresponding normal tissues as potential biomarkers. A total of 36 patients with laryngeal squamous cell carcinoma were recruited. Four of these cases were randomly selected for cDNA microarray analysis of the entire genome. Using semi-qu ...[more]

PMID: 23226807

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Project description:Understanding the molecular mechanisms and gene expression in laryngeal squamous cell carcinoma (LSCC) may explain its aggressive biological behavior and regional metastasis pathways. In the present study, patients with locally advanced LSCC tumors were examined for differential gene expression in the normal mucosa (non-tumoral mucosa), tumors and lymph node tissues. The aim was to identify possible predictive genes for lymph node metastasis. A total of 16 patients who had undergone total laryngectomy with neck dissection for advanced LSCC were randomly selected from a hospital database: Eight of the patients had lymph node metastasis (Group 1) and the other eight patients did not have metastasis (Group 2). Overall survival (OS), disease-free survival (DFS) and disease-specific survival (DSS) were analyzed. For each patient, paraffin-embedded tissue samples were collected from non-tumoral mucosa, tumoral lesions and lymph node tissues. RNA was extracted from the tissue samples and used for complementary DNA synthesis, and microarray analysis was subsequently performed on each sample. Gene expression levels were determined in each specimen, and Groups 1 and 2 were compared and statistically analyzed. The microarray results for lymph node metastasis-positive and -negative groups, indicated the differential expression of 312 genes in the lymph nodes, 691 genes in the normal mucosal tissue and 93 genes in the tumor tissue. Transgelin (TAGLN) and cofilin 1 (CFL1) were identified as possible target genes and validated using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). The RT-qPCR results for TAGLN and CFL1 supported the microarray data. OS, DFS and DSS times were longer in Group 2 than in Group 1 (P=0.002, 0.015 and 0.009, respectively). In addition, TAGLN and CFL1 were associated with DFS and DSS. On the basis of these results, it is suggested that TAGLN and CFL1 expression may play an important role in the pathogenesis of regional metastasis and poor prognosis in advanced LSCC.

Project description:Aberrant methylated genes (DMGs) play an important role in the etiology and pathogenesis of esophageal squamous cell carcinoma (ESCC). In this study, we aimed to integrate three cohorts profile datasets to ascertain aberrant methylated-differentially expressed genes and pathways associated with ESCC by comprehensive bioinformatics analysis. We downloaded data of gene expression microarrays (GSE20347, GSE38129) and gene methylation microarrays (GSE52826) from the Gene Expression Omnibus (GEO) database. Aberrantly differentially expressed genes (DEGs) were obtained by GEO2R tool. The David database was then used to perform Gene ontology (GO) analysis and Kyoto Encyclopedia of Gene and Genome pathway enrichment analyses on selected genes. STRING and Cytoscape software were used to construct a protein-protein interaction (PPI) network, then the modules in the PPI networks were analyzed with MCODE and the hub genes chose from the PPI networks were verified by Oncomine and TCGA database. In total, 291 hypomethylation-high expression genes and 168 hypermethylation-low expression genes were identified at the screening step, and finally found six mostly changed hub genes including KIF14, CDK1, AURKA, LCN2, TGM1, and DSG1. Pathway analysis indicated that aberrantly methylated DEGs mainly associated with the P13K-AKT signaling, cAMP signaling and cell cycle process. After validation in multiple databases, most hub genes remained significant. Patients with high expression of AURKA were associated with shorter overall survival. To summarize, we have identified six feasible aberrant methylated-differentially expressed genes and pathways in ESCC by bioinformatics analysis, potentially providing valuable information for the molecular mechanisms of ESCC. Our data combined the analysis of gene expression profiling microarrays and gene methylation profiling microarrays, simultaneously, and in this way, it can shed a light for screening and diagnosis of ESCC in future.

Project description:ObjectiveTo analyze the differentially expressed genes (DEGs) between lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) with bioinformatics analysis and search for potential biomarkers for clinical diagnosis of nonsmall cell lung cancer (NSCLC).MethodsThe gene expression profiling datasets of LUAD and LUSC were acquired. The transcriptome differences between LUAD and LUSC were identified using R language processing and t-test analysis. The differential expressions of the genes were shown by Venn diagram. The DEGs identified by GEO2R were analyzed with DAVID and Ingenuity Pathway Analysis (IPA) to identify the signaling pathways and biomarkers that could be used for differential diagnosis of LUAD and LUSC. The TCGA data and the biomarker expression data from clinical lung cancer samples were used to verify the differential expressions of the Osteoarthritis pathway and LXR/RXR between LUAD and LUSC. We further examined the differential expressions of miR-181 and its two target genes, WNT5A and MBD2, in 23 clinical specimens of lung squamous cell carcinoma and the paired adjacent tissues.ResultsGEO data analysis identified 851 DEGs (including 276 up-regulated and 575 down-regulated genes) in LUAD and 885 DEGs (including 406 up-regulated and 479 down-regulated genes) in LUSC. DAVID and IPA analysis revealed that leukocyte migration and inflammatory responses were more abundant in LUAD than in LUSC. Osteoarthritis pathway was inhibited in LUAD and activated in LUSC. IPA analysis showed that transcription factors (GATA4, RELA, YBX1, TP63 and MBD2), cytokines (WNT5A and IL1A) and microRNAs (miR-34a, miR-181b and miR-15a) differed significantly between LUAD and LUSC. miR-34a with IL-1A, miR-15a with YBX1, and miR-181b with WNT5A and MBD2 could serve as the paired microRNA and mRNA targets for differential diagnosis of NSCLC subtypes. Analysis of the clinical samples showed an increased expression of miR-181b-5p and the down-regulation of WNT5A, which could be used as molecular markers for the diagnosis of LUSC.ConclusionsThrough transcriptome analysis, we identified candidate genes, paired microRNAs and pathways for differentiating LUAD and LUSC, and they can provide novel differential diagnosis and therapeutic strategies for LUAD and LUSC.

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Detection of differentially expressed genes and association with clinicopathological features in laryngeal squamous cell carcinoma.

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Detection of differentially expressed genes and association with clinicopathological features in laryngeal squamous cell carcinoma.

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