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Biomedical subjects

Mario Medvedovic

Publications and source records attributed to Mario Medvedovic.

25 records · Page 2Linked to original sources
PubMed2004

Gene expression profiles of mouse aorta and cultured vascular smooth muscle cells differ widely, yet show common responses to dioxin exposure.

Exposure to environmental toxicants may play a role in the onset and progression of cardiovascular disease. Many environmental agents, such as dioxin, are risk factors for atherosclerosis because they may exacerbate an underlying disease by altering gene expression patterns. Expression profiling of vascular tissues allows the simultaneous analysis of thousands of genes and may provide predictive information particularly useful in early disease stages. Often, however, in vivo experiments are unfeasible for material or ethical reasons, and data from cultured cells must be used instead, even though it may not be known whether cultured cells and live tissues share common global responses to the same toxicant. In a search for genes responsive to dioxin exposure, we used oligonucleotide microarrays with DNA sequences from 13,433 genes to compare global gene expression profiles of C57BL/6 mice aortas with cultured vascular smooth muscle cells (vSMCs) of the same mice. Aorta segments and vSMCs differed in the expression of more than 4500 genes, many showing expression differences greater than 1000-fold. Integration of microarray data into Gene Ontology Project annotations showed that many of the genes differentially expressed belonged to the same biological process or metabolic pathway. Notwithstanding these results, a subset of 35 genes responded in the same fashion to dioxin exposure in both systems. Genes in this subset encoded phase I and phase II detoxification enzymes, signal transduction kinases and phosphatases, and proteins involved in DNA repair and the cell cycle. We conclude that vSMCS may be useful aorta surrogates to study early gene expression responses to dioxin exposure, provided that analyses focus on this subset of genes.

Animals↗
PubMed2004

Microarray results improve significantly as hybridization approaches equilibrium.

Dual-channel long oligonucleotide microarrays are in widespread use. Although much attention has been given to proper experimental design and analysis regarding long oligonucleotide microarrays, relatively little information is available concerning the optimization of protocols. We carried out a series of microarray experiments designed to investigate the effects of different levels of target concentration and hybridization times using a long oligonucleotide library. Based on principles developed from nucleic acid renaturation kinetics studies, we show that increasing the time of hybridization from 18 h to 42 h and 66 h, especially when lower than optimal concentrations of target were used, significantly improved the quality of the microarray results. Longer hybridization times significantly increased the number of spots detected, signal-to-noise ratios, and the number of differentially expressed genes and correlations among replicate arrays. We conclude that at 18 h of incubation, target-to-probe hybridization has not reached equilibrium and that a relatively high proportion of nonspecific hybridization occurs. This result is striking, given that most, if not all, published microarray protocols stipulate 8-24 h for hybridization. Using shorter than optimal hybridization times (i.e., not allowing hybridization to reach equilibrium) has the consequence of underestimating the fold change of differentially expressed genes and of missing less represented sequences.

Algorithms↗
PubMed2003

4-aminobiphenyl-induced liver and urinary bladder DNA adduct formation in Cyp1a2(-/-) and Cyp1a2(+/+) mice.

BACKGROUND: Metabolites of the potent human carcinogen 4-aminobiphenyl (ABP) induce oxidative stress and form DNA adducts that are associated with hepatic and urinary bladder toxicity and bladder tumorigenesis. Results of in vitro and cell culture studies have suggested that cytochrome P450 1A2 (CYP1A2) is the major metabolic activator of ABP. We used Cyp1a2(-/-) knockout mice to examine the role of CYP1A2 in ABP-DNA adduct formation in the liver and the bladder. METHODS: Cyp1a2(+/+) wild-type and Cyp1a2(-/-) mice (total of four mice per group) were treated topically with 10 mg/kg ABP for various times, with or without pretreatment with 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), an inducer of CYP1A2 activity. We evaluated ABP-induced toxicity by carrying out quantitative histology (of the liver, skin, and bladder), oxidative stress by measuring hepatic thiol levels, and liver and bladder DNA adduct formation by using 32P-postlabeling. Data were analyzed by general linear models and analysis of variance. All statistical tests were two-sided. RESULTS: At the experimental times selected, we observed no histologic evidence of toxicity in the liver, skin, or bladder. Overall, Cyp1a2(+/+) mice had fewer DNA adducts 24 hours after ABP treatment than similarly treated Cyp1a2(-/-) mice. Compared with male mice, female mice had more DNA adducts in the liver but fewer adducts in the bladder, regardless of Cyp1a2 genotype. TCDD pretreatment was associated with a decrease in ABP-DNA adduct levels overall. After 2 hours of ABP treatment, hepatic thiol levels underwent statistically significant declines of severalfold in Cyp1a2(+/+) and Cyp1a2(-/-) males and in Cyp1a2(-/-) females. CONCLUSIONS: Contrary to our expectations, CYP1A2 expression was not associated with ABP-induced hepatic oxidative stress or with ABP-DNA adduct formation. Either CYP1A2 is not the major metabolic activator of ABP or other enzymes metabolically activate ABP in mice in the absence of CYP1A2.

Aminobiphenyl Compounds↗
PubMed2003

Clustering gene-expression data with repeated measurements.

Clustering is a common methodology for the analysis of array data, and many research laboratories are generating array data with repeated measurements. We evaluated several clustering algorithms that incorporate repeated measurements, and show that algorithms that take advantage of repeated measurements yield more accurate and more stable clusters. In particular, we show that the infinite mixture model-based approach with a built-in error model produces superior results.

Algorithms↗
PubMed2002

Bayesian infinite mixture model based clustering of gene expression profiles.

MOTIVATION: The biologic significance of results obtained through cluster analyses of gene expression data generated in microarray experiments have been demonstrated in many studies. In this article we focus on the development of a clustering procedure based on the concept of Bayesian model-averaging and a precise statistical model of expression data. RESULTS: We developed a clustering procedure based on the Bayesian infinite mixture model and applied it to clustering gene expression profiles. Clusters of genes with similar expression patterns are identified from the posterior distribution of clusterings defined implicitly by the stochastic data-generation model. The posterior distribution of clusterings is estimated by a Gibbs sampler. We summarized the posterior distribution of clusterings by calculating posterior pairwise probabilities of co-expression and used the complete linkage principle to create clusters. This approach has several advantages over usual clustering procedures. The analysis allows for incorporation of a reasonable probabilistic model for generating data. The method does not require specifying the number of clusters and resulting optimal clustering is obtained by averaging over models with all possible numbers of clusters. Expression profiles that are not similar to any other profile are automatically detected, the method incorporates experimental replicates, and it can be extended to accommodate missing data. This approach represents a qualitative shift in the model-based cluster analysis of expression data because it allows for incorporation of uncertainties involved in the model selection in the final assessment of confidence in similarities of expression profiles. We also demonstrated the importance of incorporating the information on experimental variability into the clustering model. AVAILABILITY: The MS Windows(TM) based program implementing the Gibbs sampler and supplemental material is available at http://homepages.uc.edu/~medvedm/BioinformaticsSupplement.htm CONTACT: medvedm@email.uc.edu

Bayes Theorem↗
PubMed2002

Isozyme-specific abnormalities of PKC in thyroid cancer: evidence for post-transcriptional changes in PKC epsilon.

PKC isozymes are the major binding proteins for tumor-promoting phorbol esters, and PKC activity is abnormal in a number of different human cancers. Less is known about putative structural and functional changes of specific PKC isozymes in human neoplasms. A single-point mutation of PKCalpha at position 881 of the coding sequence has been observed in human pituitary adenomas and up to 50% of thyroid follicular neoplasms, and a rearrangement of PKCepsilon was reported in a thyroid follicular carcinoma cell line, suggesting that these signaling proteins may play a role in thyroid tumorigenesis. To explore this possibility, we examined thyroid neoplasms for mutations and changes in expression levels of PKCepsilon or alpha. None of the 57 follicular adenomas, 26 papillary carcinomas (PCs), 7 follicular carcinomas, or the anaplastic carcinoma harbored the PKCalpha 881A>G mutation. Moreover, none of 15 PCs, 10 follicular adenomas, or 6 follicular carcinomas showed evidence of mutations of PKCepsilon. However, 8 of 11 PCs had major isozyme-specific reductions of the PKCepsilon protein, which occurred through either translational or posttranslational mechanisms. These data indicate that post-transcriptional changes in PKCepsilon are highly prevalent in thyroid tumors and may play a significant role in their development.

Adenoma↗