PURPOSE: Apoptosis is a physiological mechanism for deleting cells from the body for development and homeostasis. Exogenous cytokines such as tumor necrosis factor alpha (TNFalpha) and transforming growth factor beta (TGF beta) are known to modulate apoptosis, thus can provide a new therapeutic modality for various malignancies. We studied whether TNFalpha or TGFbeta can induce apoptosis or exert antiproliferative effect on human gastric cancer cell line (AGS) and which genes are involved in the cytokine-induced apoptotic pathway. MATERIALS AND METHODS: To examine the effect of TNFalpha or TGF beta on AGS cell line (human gastric adenocarcimoma), we performed following tests; MTT test, trypan blue dye exclusion assay and colony forming efficiency. Total DNA was extracted from the TNFalpha-treated AGS cells and DNA ladder was detected as the hallmark of apoptosis, and flow cytometry analysis was performed for another apoptotic index. The effects of TNFalpha on c-myc expression was observed using RT-PCR. RESULTS: TNFalpha suppressed AGS cell growth, in a time- and dose-dependent manner, but TGFbeta had no effect on AGS cell growth. Electrophoretic analysis of total cellular DNA revealed the pattern of internucleosomal DNA cleavage, which is specific for apoptosis and the effect was observed from 24 to 72 hrs after 50 ng/ml TNFalpha treatment. Time-dependent increse of apoptotic cells by TNFalpha was detected by flow cytometry analysis. Morphological changes such as cell to cell contacts and extension of cell processes were observed in TNFalpha-treated AGS cells. RT-PCR using c-myc primers showed thatthe mRNA levels were increased 6 hrs after TNFalpha treatment and persisted for 72 hrs. CONCLUSION: It is suggested that TNFalpha, but not TGF beta, functions as an important inducer of apoptosis in AGS cell line, and c-myc may function as a critical endogenous activator of the pathway leading to cell death of AGS cells.
Apoptosis* ; Cell Death ; Cell Line ; Cytokines ; DNA ; DNA Cleavage ; Flow Cytometry ; Homeostasis ; Humans ; RNA, Messenger ; Stomach Neoplasms* ; Stomach* ; Transforming Growth Factor beta* ; Trypan Blue ; Tumor Necrosis Factor-alpha

Numerous studies have reported that genes with similar expression patterns are co-regulated. From gene expression data, we have assumed that genes having similar expression pattern would share similar transcription factor binding sites (TFBSs). These function as the binding regions for transcription factors (TFs) and thereby regulate gene expression. In this context, various analysis tools have been developed. However, they have shortcomings in the combined analysis of expression patterns and significant TFBSs and in the functional analysis of target genes of significantly overrepresented putative regulators. In this study, we present a web-based A Functional Clustering Analysis Tool for Predicted Transcription Regulatory Elements and Gene Ontology Terms (FCAnalyzer). This system integrates microarray clustering data with similar expression patterns, and TFBS data in each cluster. FCAnalyzer is designed to perform two independent clustering procedures. The first process clusters gene expression profiles using the K-means clustering method, and the second process clusters predicted TFBSs in the upstream region of previously clustered genes using the hierarchical biclustering method for simultaneous grouping of genes and samples. This system offers retrieved information for predicted TFBSs in each cluster using Match(TM) in the TRANSFAC database. We used gene ontology term analysis for functional annotation of genes in the same cluster. We also provide the user with a combinatorial TFBS analysis of TFBS pairs. The enrichment of TFBS analysis and GO term analysis is statistically by the calculation of P values based on Fisher's exact test, hypergeometric distribution and Bonferroni correction. FCAnalyzer is a web-based, user-friendly functional clustering analysis system that facilitates the transcriptional regulatory analysis of co-expressed genes. This system presents the analyses of clustered genes, significant TFBSs, significantly enriched TFBS combinations, their target genes and TFBS-TF pairs.
Binding Sites ; Cluster Analysis* ; Gene Expression ; Gene Ontology* ; Transcription Factors ; Transcriptome