BackgroundMany prediction tools for microRNA (miRNA) targets have been developed, but inconsistent predictions were observed across multiple algorithms, which can make further analysis difficult. Moreover, the nomenclature of human miRNAs changes rapidly. To address these issues, we developed a web-based system, miRSystem, for converting queried miRNAs to the latest annotation and predicting the function of miRNA by integrating miRNA target gene prediction and function/pathway analyses.ResultsFirst, queried miRNA IDs were converted to the latest annotated version to prevent potential conflicts resulting from multiple aliases. Next, by combining seven algorithms and two validated databases, potential gene targets of miRNAs and their functions were predicted based on the consistency across independent algorithms and observed/expected ratios. Lastly, five pathway databases were included to characterize the enriched pathways of target genes through bootstrap approaches. Based on the enriched pathways of target genes, the functions of queried miRNAs could be predicted.ConclusionsMiRSystem is a user-friendly tool for predicting the target genes and their associated pathways for many miRNAs simultaneously. The web server and the documentation are freely available at http://mirsystem.cgm.ntu.edu.tw/.
Background: Although cigarette smoking is the major risk factor for lung cancer, only 7% of female lung cancer patients in Taiwan have a history of smoking. The genetic mechanisms of carcinogenesis in nonsmokers are unclear, but semaphorins have been suggested to play a role as lung tumor suppressors. This report is a comprehensive analysis of the molecular signature of nonsmoking female lung cancer patients in Taiwan, with a particular focus on the semaphorin gene family.Methods: Sixty pairs of tumor and adjacent normal lung tissue specimens were analyzed by using Affymetrix U133plus2.0 expression arrays. Differentially expressed genes in tumor tissues were identified by a paired t test and validated by reverse transcriptase-PCR and immunohistochemistry. Functional analysis was conducted by using Ingenuity Pathway Analysis as well as gene set enrichment analysis and sigPathway algorithms. Kaplan-Meier survival analyses were used to evaluate the association of SEMA5A expression and clinical outcome.Results: We identified 687 differentially expressed genes in non-small cell lung carcinoma (NSCLC). Many of these genes, most notably the semaphorin family, were participants in the axon guidance signaling pathway. The downregulation of SEMA5A in tumor tissue, both at the transcriptional and translational levels, was associated with poor survival among nonsmoking women with NSCLC.Conclusions: In summary, several semaphorin gene family members were identified as potential therapeutic targets, and SEMA5A may be useful as a prognostic biomarker for NSCLC, which may also be gender specific in Taiwanese patients.Impact: A novel biomarker for NSCLC is identified. Cancer Epidemiol Biomarkers Prev; 19(10); 2590-7. ©2010 AACR.
Studies were conducted to determine whether gene expression profiles following a single dose of radiation would yield equivalent profiles following fractionated radiation in different tumor cell lines. MCF7 (breast), DU145 (prostate), and SF539 (gliosarcoma) cells were exposed to a total radiation dose of 10 Gy administered as a single dose (SD) or by daily multifractions (MF) of 5 Â 2 Gy. Following radiation treatment, mRNA was isolated at 1, 4, 10, and 24 h and processed for cDNA microarray analysis. To determine the influence of the tumor microenvironment on gene expression, one cell type (DU145) was evaluated growing as a solid tumor in athymic nude mice for both radiation protocols. Unsupervised hierarchical cluster map analysis showed significant differences in gene expression profiles between SD and MF treatments for cells treated in vitro, with MF yielding a more robust induction compared with SD. Several genes were uniquely up-regulated by MF treatment, including multiple IFN-related genes (STAT1, G1P2, OAS1, OAS3, G1P3, IFITM1) and TGF-b-associated genes (EGR1, VEGF, THBS1, and TGFB2). DU145 cells grown in vivo exhibited a completely different set of genes induced by both SD and MF compared with the same cells exposed in vitro. The results of the study clearly show distinct differences in the molecular response of cells between SD and MF radiation exposures and show that the tumor microenvironment can significantly influence the pattern of gene expression after radiation exposures. [Cancer Res 2007;67(8):3845-52]
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