Biomedical subjects

Chad Creighton

Publications and source records attributed to Chad Creighton.

4 recordsLinked to original sources

PubMed2003

Profiling of pathway-specific changes in gene expression following growth of human cancer cell lines transplanted into mice.

BACKGROUND: Tumor cells cultured in vitro are widely used to investigate the molecular biology of cancers and to evaluate responses to drugs and other agents. The full extent to which gene expression in cancer cells is modulated by extrinsic factors and by the microenvironment in which the cancer cells reside remains to be determined. Two cancer cell lines (A549 lung adenocarcinoma and U118 glioblastoma) were transplanted subcutaneously into immunodeficient mice to form tumors. Global gene-expression profiles of the tumors were determined, based on analysis of expression of human genes, and compared with expression profiles of the cell lines grown in culture. RESULTS: A bioinformatics approach associated genes that showed changes in their expression levels with functional classes as defined by either the GO gene annotations or MeSH terms in the literature. The classes of genes expressed at higher levels in cells grown in vitro indicated increased cell division and metabolism, reflecting the more favorable environment for cell proliferation. In contrast, in vivo tumor growth resulted in upregulation of a significant number of genes involved in the extracellular matrix (ECM), cell adhesion, cytokine and metalloendopeptidase activity, and neovascularization. When placed in comparable tissue environments, the U118 cells and the A549 cells expressed different sets of ECM and cell adhesion-related genes, suggesting different mechanisms of extracellular interaction at work in the different cancers. CONCLUSIONS: Studies of this type allow us to examine the specific contribution of cancer cells to gene expression patterns within an in vivo tumor mixed with non-cancerous tissue.

Animals↗

PubMed2003

Gene expression patterns define pathways correlated with loss of differentiation in lung adenocarcinomas.

An analysis of microarray data from 86 lung adenocarcinomas reveals hundreds of genes significantly correlated with tumor cell differentiation. A bioinformatics approach of linking these genes to public information from the Locuslink and KEGG databases yields evidence for a loss of tumor cell differentiation being associated with biological processes of cell division, protein degradation, pyrimidine and purine metabolism, oxidative phosphorylation, glyoxylate and dicarboxylate metabolism, folate biosynthesis, and glutamate metabolism. The increased expression of genes involved in these processes is consistent with increased proliferation and metabolism characteristics of poorly differentiated tumors. The complete results of this analysis are available at http://dot.ped.med.umich.edu:2000/pub/diff/index.htm.

Adenocarcinoma↗

PubMed2003

Mining gene expression databases for association rules.

MOTIVATION: Global gene expression profiling, both at the transcript level and at the protein level, can be a valuable tool in the understanding of genes, biological networks, and cellular states. As larger and larger gene expression data sets become available, data mining techniques can be applied to identify patterns of interest in the data. Association rules, used widely in the area of market basket analysis, can be applied to the analysis of expression data as well. Association rules can reveal biologically relevant associations between different genes or between environmental effects and gene expression. An association rule has the form LHS --> RHS, where LHS and RHS are disjoint sets of items, the RHS set being likely to occur whenever the LHS set occurs. Items in gene expression data can include genes that are highly expressed or repressed, as well as relevant facts describing the cellular environment of the genes (e.g. the diagnosis of a tumor sample from which a profile was obtained). RESULTS: We demonstrate an algorithm for efficiently mining association rules from gene expression data, using the data set from Hughes et al. (2000, Cell, 102, 109-126) of 300 expression profiles for yeast. Using the algorithm, we find numerous rules in the data. A cursory analysis of some of these rules reveals numerous associations between certain genes, many of which make sense biologically, others suggesting new hypotheses that may warrant further investigation. In a data set derived from the yeast data set, but with the expression values for each transcript randomly shifted with respect to the experiments, no rules were found, indicating that most all of the rules mined from the actual data set are not likely to have occurred by chance. AVAILABILITY: An implementation of the algorithm using Microsoft SQL Server with Access 2000 is available at http://dot.ped.med.umich.edu:2000/pub/assoc_rules/assoc_rules.zip. Our results from mining the yeast data set are available at http://dot.ped.med.umich.edu:2000/pub/assoc_rules/yeast_results.zip.

Algorithms↗

PubMed2003

Expression of matrix metalloproteinase 9 (MMP-9/gelatinase B) in adenocarcinomas strongly correlated with expression of immune response genes.

Matrix metalloproteinases (MMPs) are endopeptidases considered to be important regulators of the microenvironment of cancer. While MMPs are traditionally associated with the extracellular matrix (ECM), here we provide new evidence from an analysis of gene expression profiles from human tumor tissue that MMP-9 (gelatinase B) is associated with elements of the immune system in a way analogous to the association of other MMPs, such as MMP-2 (gelatinase A), with components of the ECM. An analysis of three independent microarray datasets of lung adenocarcinomas from previous studies [Nat. Med. 8, 816-824 (2002); Proc. Natl. Acad. Sci. USA 98, 13790-13795 (2001); Proc. Natl. Acad. Sci. USA, 98, 13784-13789 (2001)] showed that, in each dataset, out of the set of genes with significant correlations in mRNA expression to the expression of MMP9 (P < 0.005), a highly disproportionate number were found to be annotated in the Locuslink database as having a role in the anti-pathogen response. By comparison, out of the set of genes significantly correlated with the expression of MMP2, a highly disproportionate number were known components of the ECM. The same patterns observed in the lung data for both MMP2 and MMP9 were found as well in an additional published dataset of colon and ovarian adenocarcinomas [Am. J. Pathol. 159, 1231-1238 (2001)]. The results of this study suggest a greater functional role for MMP-9 in the immune response to cancer than what may previously have been thought.

Adenocarcinoma↗