Min Zhao

Expression of programmed cell death 5 gene involves in regulation of apoptosis in gastric tumor cells

The protein of programmed cell death 5 (PDCD5) is believed to participate in regulation of apoptosis. Although PDCD5 is reducibly expressed in various human tumors, it is not clear which expression level of PDCD5 is in gastric cancer (GC). In this study, we have systematically employed the approaches of RT-PCR, Real- time PCR, Immunohistochemistry (IHC), Immunofluorescence staining (IFS) and Western blot to determine the PDCD5 expression in GC cells and primary tumors, at mRNA and protein level, respectively. Our data revealed that the positive rate of PDCD5 expression in the gastric tumor tissues was significantly less than that of the normal tissues (14 out of 102 vs 36 out of 51), whereas, the decreased expression of PDCD5 protein was well correlated with the up-regulated expression of Bcl-2 in these tissues, and the up-regulated expression and nuclear translocation of PDCD5 protein were verified in the apoptotic GC cells induced by Diallyl trisulfide (DATS). Furthermore, the survival curve has suggested that the more PDCD5 expressions were found in the patients, the longer the survival periods were. Therefore, our observations lay down a reasonable postulation that PDCD5 may play a key role to regulate the apoptotic processes in the GC cells and gastric tumors.

TSdb: A database of transporter substrates linking metabolic pathways and transporter systems on a genome scale via their shared substrates

TSdb (http://tsdb.cbi.pku.edu.cn) is the first manually curated central repository that stores formatted information on the substrates of transporters. In total, 37608 transporters with 15075 substrates from 884 organisms were curated from UniProt functional annotation. A unique feature of TSdb is that all the substrates are mapped to identifiers from the KEGG Ligand compound database. Thus, TSdb links current metabolic pathway schema with compound transporter systems via the shared compounds in the pathways. Furthermore, all the transporter substrates in TSdb are classified according to their biochemical properties, biological roles and subcellular localizations. In addition to the functional annotation of transporters, extensive compound annotation that includes inhibitor information from the KEGG Ligand and BRENDA databases has been integrated, making TSdb a useful source for the discovery of potential inhibitory mechanisms linking transporter substrates and metabolic enzymes. User-friendly web interfaces are designed for easy access, query and download of the data. Text and BLAST searches against all transporters in the database are provided. We will regularly update the substrate data with evidence from new publications.

EDdb: A web resource for eating disorder and its application to identify an extended adipocytokine signaling pathway related to eating disorder

Eating disorder is a group of physiological and psychological disorders affecting approximately 1% of the female population worldwide. Although the genetic epidemiology of eating disorder is becoming increasingly clear with accumulated studies, the underlying molecular mechanisms are still unclear. Recently, integration of various high-throughput data expanded the range of candidate genes and started to generate hypotheses for understanding potential pathogenesis in complex diseases. This article presents EDdb (Eating Disorder database), the first evidence-based gene resource for eating disorder. Fifty-nine experimentally validated genes from the literature in relation to eating disorder were collected as the core dataset. Another four datasets with 2824 candidate genes across 601 genome regions were expanded based on the core dataset using different criteria (e.g., protein-protein interactions, shared cytobands, and related complex diseases). Based on human protein-protein interaction data, we reconstructed a potential molecular sub-network related to eating disorder. Furthermore, with an integrative pathway enrichment analysis of genes in EDdb, we identified an extended adipocytokine signaling pathway in eating disorder. Three genes in EDdb (ADIPO (adiponectin), TNF (tumor necrosis factor) and NR3C1 (nuclear receptor subfamily 3, group C, member 1)) link the KEGG (Kyoto Encyclopedia of Genes and Genomes) “adipocytokine signaling pathway” with the BioCarta “visceral fat deposits and the metabolic syndrome” pathway to form a joint pathway. In total, the joint pathway contains 43 genes, among which 39 genes are related to eating disorder. As the first comprehensive gene resource for eating disorder, EDdb (http://eddb.cbi.pku.edu.cn) enables the exploration of gene-disease relationships and cross-talk mechanisms between related disorders. Through pathway statistical studies, we revealed that abnormal body weight caused by eating disorder and obesity may both be related to dysregulation of the novel joint pathway of adipocytokine signaling. In addition, this joint pathway may be the common pathway for body weight regulation in complex human diseases related to unhealthy lifestyle.

Downregulation of 425G>A variant of calcium-binding protein S100A14 associated with poor differentiation and prognosis in gastric cancer

PurposeAltered level of S100 calcium-binding proteins is involved in tumor development and progression. However, their role in gastric cancer (GC) is not well documented. We investigated the expression pattern of S100 proteins and differentiation or prognosis as well as possible mechanisms in GC.MethodsRT-PCR, Western blot analysis, and immunohistochemistry were used to determine the mRNA and protein expression of S100 family genes in GC. The polymorphisms of promoter and 5′-UTR of S100A14 gene were identified and related to luciferase reporter gene activity. Association of S100A14 expression with clinicopathologic features and survival in GC was analyzed.ResultsWe detected upregulated S100A2, S100A6, S100A10, and S100A11 expression and downregulated S100P and S100B expression in GC. Particularly, we detected differential mRNA and protein expression of S100A14 in GC cell lines and primary tumors. Furthermore, S100A14 expression change was related to a differentiated GC phenotype, with an expression in 31/40 (77.5xa0%) samples of well-differentiated tumors and 29/85 (34.1xa0%) samples of poorly differentiated tumors (Pxa0<xa00.001). Moreover, 5-year survival was better in GC cases with positive than negative S100A14 level (Pxa0=xa00.02). The genetic variant 425G>A on the 5′-UTR of S100A14 was associated with reduced S100A14 expression in GC cells.ConclusionDecreased expression of S100A14 with presence of its genetic variant 425G>A may be associated with an undifferentiated phenotype and poor prognosis in GC.

Identification of differentially-expressed genes in intestinal gastric cancer by microarray analysis.

Gastric cancer (GC) is one of the most frequent malignant tumors. In order to systematically characterize the cellular and molecular mechanisms of intestinal GC development, in this study, we used 22 K oligonucleotide microarrays and bioinformatics analysis to evaluate the gene expression profiles of GC in 45 tissue samples, including 20 intestinal GC tissue samples, 20 normal appearing tissues (NATs) adjacent to tumors and 5 noncancerous gastric mucosa tissue samples. These profiles allowed us to explore the transcriptional characteristics of GC and determine the change patterns in gene expression that may be of clinical significance. 1519 and 1255 differentially-expressed genes (DEGs) were identified in intestinal GC tissues and NATs, respectively, as determined by Bayesian analysis (P < 0.001). These genes were associated with diverse functions such as mucosa secretion, metabolism, proliferation, signaling and development, which occur at different stages of GC development.

METSP: A Maximum-Entropy Classifier Based Text Mining Tool for Transporter-Substrate Identification with Semistructured Text

The substrates of a transporter are not only useful for inferring function of the transporter, but also important to discover compound-compound interaction and to reconstruct metabolic pathway. Though plenty of data has been accumulated with the developing of new technologies such as in vitro transporter assays, the search for substrates of transporters is far from complete. In this article, we introduce METSP, a maximum-entropy classifier devoted to retrieve transporter-substrate pairs (TSPs) from semistructured text. Based on the high quality annotation from UniProt, METSP achieves high precision and recall in cross-validation experiments. When METSP is applied to 182,829 human transporter annotation sentences in UniProt, it identifies 3942 sentences with transporter and compound information. Finally, 1547 confidential human TSPs are identified for further manual curation, among which 58.37% pairs with novel substrates not annotated in public transporter databases. METSP is the first efficient tool to extract TSPs from semistructured annotation text in UniProt. This tool can help to determine the precise substrates and drugs of transporters, thus facilitating drug-target prediction, metabolic network reconstruction, and literature classification.

Effects of garlic oil on tumoragenecity and intercellular communication in human gastric cancer cell line

Previous studies have demonstrated that garlic oil (GO) and its anti-tumor compound could inhibit DNA and RNA synthesis in human cancer cells. In order to explore the effects of garlic oil on carcinoma cells, a gastric carcinoma cell line, BGC-823 was studied at cellular and molecular levels after garlic oil treatment. Data showed that the cell differentiation and suppression of tumorigenicity were significantly induced in tumor cells after garlic oil treatment. There was a correlation between the cell-cell communication recovery and the increase of p53 and waf1/p21 gene expression in garlic oil-treated cells. This result suggested that tumor suppressor gene waf1/p21 and wt p53 might play an important role in this effect.

Mutations analysis ofSTK 11 gene in Chinese families with Peutz-Jeghers syndrome

Peutz-Jeghers syndrome (PJS) is an autosomal dominantly inherited disease characterized by multiple gastrointestinal hamartomatous polyps and melanin spots on lips and buccal mucosa, with an increased risk for various cancers. The PJS gene, a potential tumour suppressor gene, encoding a serine/ threonie kinase (STK11), was mapped to chromosome 19p13.3. To investigate the mutations ofSTK11 gene in Chinese with PJS, we analyzed its coding sequence in fifteen patients and twenty unaffected members of six families, including three multigenerational families with PJS and three sporadic families with PJS, by PCR, PCR-DHPLC and DNA sequencing techniques. Ten point mutations were found in the six families, including five missense mutations, one acceptor-splice site mutation, a nonsense mutation and three silent mutations. Our data showed that five missense mutations occurrd at codon 123 (CAG to CAT) in exon 2, codon 161 (ATT to AGT) in exon 4, codon 194 (GAC to GAG) in exon 4, codon 245 (CTC to TTC) in exon 5 and codon 354 (TTC to TTG) in exon 8. One kind of nonsense mutation was detected at codon 37 (CAG to TAG) in exon 1. Furthermore, we found an intronic mutation at a splice-acceptor site: a one base substitution from AG to A4 in intron 4. These mutations were not detected in 20 normal DNA samples. In three sporadic families, only in one patient, we detected a missense mutation in exon 5. In addition, we found three silent mutations, which may cause polymorphisms ofSTK11 gene in introns l(+36), 3(−51) and 5(+27). These results indicated that the point mutation inSTK11 might be involved in PJS patho-genesis. Mutation frequency is higher in the families suffering PJS in three or more generations than that of the sporadic cases.