Identification of molecular mechanisms of glutamine in pancreatic cancer

The aim of the present study was to explore the critical genes and molecular mechanisms in pancreatic cancer (PC) cells with glutamine. By analyzing microarray data GSE17632 from the Gene Expression Omnibus database, the DEGs between PC cells treated with glutamine and without glutamine were evaluated. Additionally, function enrichment analyses and protein-protein interaction (PPI) network construction of DEGs were performed. Network module and literature mining analyses were performed to analyze the critical DEGs in PC cells. In total, 495 genes were selected as DEGs between control and glutamine cells in PC. These DEGs were mainly enriched in several Gene Ontology (GO) terms in biological process, cellular components and molecular function. Additionally, they were also enriched in certain pathways, including metabolic pathways and the Janus kinase-signal transducer and activator of transcription (JAK-STAT) signaling pathway. MYC, heat shock 70kDa protein 5 (HSPA5), interleukin 8 (IL8), and chemokine (C-X-C motif) receptor 4 (CXCR4) were hub genes in the PPI network. Furthermore, two sub-network modules of PPI network and two co-occurrence networks were obtained. The DEGs of MYC, HSPA5, IL18 and CXCR4 may exert important roles in molecular mechanisms of PC cells with glutamine.

Identification of potential therapeutic targets for colorectal cancer by bioinformatics analysis

The aim of the present study was to identify potential therapeutic targets for colorectal cancer (CRC). The gene expression profile GSE32323, containing 34 samples, including 17 specimens of CRC tissues and 17 of paired normal tissues from CRC patients, was downloaded from the Gene Expression Omnibus database. Following data preprocessing using the Affy and preprocessCore packages, the differentially-expressed genes (DEGs) between the two types of samples were identified with the Linear Models for Microarray Analysis package. Next, functional and pathway enrichment analysis of the DEGs was performed using the Database for Annotation Visualization and Integrated Discovery. The protein-protein interaction (PPI) network was established using the Search Tool for the Retrieval of Interacting Genes database. Utilizing WebGestalt, the potential microRNAs (miRNAs/miRs) of the DEGs were screened and the integrated miRNA-target network was built. A cohort of 1,347 DEGs was identified, the majority of which were mainly enriched in cell cycle-related biological processes and pathways. Cyclin-dependent kinase 1 (CDK1), cyclin B1 (CCNB1), MAD2 mitotic arrest deficient-like 1 (MAD2L1) and BUB1 mitotic checkpoint serine/threonine kinase B (BUB1B) were prominent in the PPI network, while the over-represented genes in the integrated miRNA-target network were SRY (sex determining region Y)-box 4 (SOX4; targeted by hsa-mir-129), v-myc avian myelocytomatosis viral oncogene homolog (MYC; targeted by hsa-let-7c and hsa-mir-145) and cyclin D1 (CCND1; targeted by hsa-let-7b). CDK1, CCNB1 and CCND1 were also associated with the p53 signaling pathway. Overall, several genes associated with the cell cycle and p53 pathway were identified as biomarkers for CRC. CDK1, CCNB1, MAD2L1, BUB1B, SOX4, collagen type I α2 chain and MYC may play significant roles in CRC progression by affecting the cell cycle-related pathways, while CDK1, CCNB1 and CCND1 may serve as crucial regulators in the p53 signaling pathway. Furthermore, SOX4, MYC and CCND1 may be targets of miR-129, hsa-mir-145 and hsa-let-7c, respectively. However, further validation of these data is required.

Identification of potential therapeutic targets for papillary thyroid carcinoma by bioinformatics analysis

The aim of the present study was to identify potential therapeutic targets for papillary thyroid carcinoma (PTC) and to investigate the possible mechanism underlying this disease. The gene expression profile, GSE53157, was downloaded from the Gene Expression Omnibus database. Only 10 chips, including 3 specimens of normal thyroid tissues and 7 specimens of well-differentiated thyroid carcinomas, were analyzed in the present study. Differentially-expressed genes (DEGs) between PTC patients and normal individuals were identified. Next, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses of DEGs were performed. Modules in the protein-protein interaction (PPI) network were identified. Significant target genes were selected from the microRNA (miRNA) regulatory network. Furthermore, the integrated network was constructed with the miRNA regulatory and PPI network modules, and key target genes were screened. A total of 668 DEGs were identified. Modules M1, M2 and M3 were identified from the PPI network. From the modules, DEGs of cyclin-dependent kinase inhibitor 1A, S100 calcium binding protein A6 (S100A6), dual specificity phosphatase 5, keratin 19, met proto-oncogene (MET) and lectin galactoside-binding soluble 3 were included in the Malacards database. In the miRNA regulatory and integrated networks, genes of cyclin-dependent kinase inhibitor 1C (CDKN1C), peroxisome proliferator-activated receptor γ, aryl hydrocarbon receptor, basic helix-loop-helix family, member e40 and reticulon 1 were the key target genes. S100A6, MET and CDKN1C may exhibit key roles in the progression and development of PTC, and may be used as specific therapeutic targets in the treatment of PTC. However, further experiments are required to confirm these results.

An approach for integrating toxicogenomic data in risk assessment: the dibutyl phthalate case study

An approach for evaluating and integrating genomic data in chemical risk assessment was developed based on the lessons learned from performing a case study for the chemical dibutyl phthalate. A case study prototype approach was first developed in accordance with EPA guidance and recommendations of the scientific community. Dibutyl phthalate (DBP) was selected for the case study exercise. The scoping phase of the dibutyl phthalate case study was conducted by considering the available DBP genomic data, taken together with the entire data set, for whether they could inform various risk assessment aspects, such as toxicodynamics, toxicokinetics, and dose-response. A description of weighing the available dibutyl phthalate data set for utility in risk assessment provides an example for considering genomic data for future chemical assessments. As a result of conducting the scoping process, two questions--Do the DBP toxicogenomic data inform 1) the mechanisms or modes of action?, and 2) the interspecies differences in toxicodynamics?--were selected to focus the case study exercise. Principles of the general approach include considering the genomics data in conjunction with all other data to determine their ability to inform the various qualitative and/or quantitative aspects of risk assessment, and evaluating the relationship between the available genomic and toxicity outcome data with respect to study comparability and phenotypic anchoring. Based on experience from the DBP case study, recommendations and a general approach for integrating genomic data in chemical assessment were developed to advance the broader effort to utilize 21st century data in risk assessment.

Use of genomic data in risk assessment case study: II. Evaluation of the dibutyl phthalate toxicogenomic data set

An evaluation of the toxicogenomic data set for dibutyl phthalate (DBP) and male reproductive developmental effects was performed as part of a larger case study to test an approach for incorporating genomic data in risk assessment. The DBP toxicogenomic data set is composed of nine in vivo studies from the published literature that exposed rats to DBP during gestation and evaluated gene expression changes in testes or Wolffian ducts of male fetuses. The exercise focused on qualitative evaluation, based on a lack of available dose-response data, of the DBP toxicogenomic data set to postulate modes and mechanisms of action for the male reproductive developmental outcomes, which occur in the lower dose range. A weight-of-evidence evaluation was performed on the eight DBP toxicogenomic studies of the rat testis at the gene and pathway levels. The results showed relatively strong evidence of DBP-induced downregulation of genes in the steroidogenesis pathway and lipid/sterol/cholesterol transport pathway as well as effects on immediate early gene/growth/differentiation, transcription, peroxisome proliferator-activated receptor signaling and apoptosis pathways in the testis. Since two established modes of action (MOAs), reduced fetal testicular testosterone production and Insl3 gene expression, explain some but not all of the testis effects observed in rats after in utero DBP exposure, other MOAs are likely to be operative. A reanalysis of one DBP microarray study identified additional pathways within cell signaling, metabolism, hormone, disease, and cell adhesion biological processes. These putative new pathways may be associated with DBP effects on the testes that are currently unexplained. This case study on DBP identified data gaps and research needs for the use of toxicogenomic data in risk assessment. Furthermore, this study demonstrated an approach for evaluating toxicogenomic data in human health risk assessment that could be applied to future chemicals.