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Biomedical subjects

Jan Komorowski

Publications and source records attributed to Jan Komorowski.

5 recordsLinked to original sources

Liver gene expression in rats in response to the peroxisome proliferator-activated receptor-alpha agonist ciprofibrate.

Fibrate class hypolipidemic drugs such as ciprofibrate activate the peroxisome proliferator-activated receptor-alpha (PPARalpha), which is involved in processes including lipid metabolism and hepatocyte proliferation in rodents. We examined the effects of ciprofibrate (50 mg/kg body wt per day for 60 days) on liver gene expression in rats using cDNA microarrays. The 60-day dosing period was chosen to elucidate both the metabolic and proliferative actions of this substance, while avoiding confounding effects from the hepatic carcinogenesis seen during more long-term stimulation. Ciprofibrate changed the expression of many genes including previously known PPARalpha agonist-responsive genes involved in processes such as lipid metabolism and inflammatory responses. In addition, many novel candidate genes involved in sugar metabolism, transcription, signal transduction, cell proliferation, and stress responses appeared to be differentially regulated in ciprofibrate-dosed rats. Ciprofibrate also resulted in significant increases in liver weight and hepatocyte proliferation. The cDNA microarray results were confirmed by Northern blot analysis for selected genes. This study thus identifies many genes that appear to be differentially regulated in ciprofibrate-dosed rats, and some of these are potential targets of PPARalpha. The functional diversity of these candidate genes suggests that most of them are likely to be differentially regulated as indirect consequence of the many processes affected by ciprofibrate in rodent liver. Although caution is advisable in the interpretation of genome-wide expression data, the genes identified in the present study provide candidates for further studies that may give new insight into the mechanisms of action of peroxisome proliferators.

Animals↗

Learning rule-based models of biological process from gene expression time profiles using gene ontology.

MOTIVATION: Microarray technology enables large-scale inference of the participation of genes in biological process from similar expression profiles. Our aim is to induce classificatory models from expression data and biological knowledge that can automatically associate genes with novel hypotheses of biological process. RESULTS: We report a systematic supervised learning approach to predicting biological process from time series of gene expression data and biological knowledge. Biological knowledge is expressed using gene ontology and this knowledge is associated with discriminatory expression-based features to form minimal decision rules. The resulting rule model is first evaluated on genes coding for proteins with known biological process roles using cross validation. Then it is used to generate hypotheses for genes for which no knowledge of participation in biological process could be found. The theoretical foundation for the methodology based on rough sets is outlined in the paper, and its practical application demonstrated on a data set previously published by Cho et al. (Nat. Genet., 27, 48-54, 2001). AVAILABILITY: The Rosetta system is available at http://www.idi.ntnu.no/~aleks/rosetta. SUPPLEMENTARY INFORMATION: http://www.lcb.uu.se/~hvidsten/bioinf_cho/

Algorithms↗

Predicting gene ontology biological process from temporal gene expression patterns.

The aim of the present study was to generate hypotheses on the involvement of uncharacterized genes in biological processes. To this end, supervised learning was used to analyze microarray-derived time-series gene expression data. Our method was objectively evaluated on known genes using cross-validation and provided high-precision Gene Ontology biological process classifications for 211 of the 213 uncharacterized genes in the data set used. In addition, new roles in biological process were hypothesized for known genes. Our method uses biological knowledge expressed by Gene Ontology and generates a rule model associating this knowledge with minimal characteristic features of temporal gene expression profiles. This model allows learning and classification of multiple biological process roles for each gene and can predict participation of genes in a biological process even though the genes of this class exhibit a wide variety of gene expression profiles including inverse coregulation. A considerable number of the hypothesized new roles for known genes were confirmed by literature search. In addition, many biological process roles hypothesized for uncharacterized genes were found to agree with assumptions based on homology information. To our knowledge, a gene classifier of similar scope and functionality has not been reported earlier.

Animals↗

Evaluation of the levels of bFGF, VEGF, sICAM-1, and sVCAM-1 in serum of patients with thyroid cancer.

Tumour growth and development depend on a complex cascade of angiogenic factors. The aim of the study is evaluation of the level of growth factors VEGF and bFGF, and adhesion molecules sICAM-1, sVCAM-1 in the serum of patients with papillary thyroid cancer. The study comprised 35 patients aged 21-68 years (mean age 46+/-14) who had papillary thyroid cancer diagnosed on the basis of thin needle aspiration biopsy, and were qualified for operative treatment. This group comprised 28 women and seven men. The control group was 26 healthy individuals. Serum concentrations of bFGF, VEGF, sICAM-1, and sVCAM-1 were evaluated by the enzyme-linked immunosorbent assay (ELISA) method. We have observed significantly higher mean concentrations of bFGF, VEGF, and sICAM-1 in the serum of patients with thyroid cancer compared with the control group. There was no significant difference between the sVCAM-1 concentrations of the thyroid cancer group and the control group.

Adult↗

Matrix metalloproteinases, tissue inhibitors of matrix metalloproteinases and angiogenic cytokines in peripheral blood of patients with thyroid cancer.

Stimulation of growth of endothelial cells from preexisting blood vessels, i.e., angiogenesis, is one of the essential elements necessary to create a permissive environment in which a tumor can grow. During angiogenesis, the matrix metalloproteinase (MMP) family of tissue enzymes contributes to normal (embriogenesis or wound repair) and pathologic tissue remodeling (chronic inflammation and tumor genesis). The proposed pathogenic roles of MMPs in cancer are tissue breakdown and remodeling during invasive tumor growth and tumor angiogenesis. Tissue inhibitors of metalloproteinases (TIMPs) form a complex with MMPs, which in turn inhibits active MMPs. Vascular endothelial growth factor (VEGF) and basic fibroblast growth factor (bFGF) are unique among mediators of angiogenesis with synergistic effect, and both can also be secreted by thyroid cancer cells. The goal of the study was to evaluate the plasma blood concentration of VEGF, bFGF, MMP-1, MMP-2, MMP-3, MMP-8, MMP-9, TIMP-1, and TIMP-2 in patients with cancer and in normal subjects. Twenty-two patients with thyroid cancers (papillary cancer, 11; partly papillary and partly follicular cancer, 3; anaplastic cancer, 5; medullary cancer, 3) and 16 healthy subjects (controls) were included in the study. VEGF, bFGF MMPs, and TIMPs were evaluated by enzyme-linked immunosorbent assay (ELISA). In patients with thyroid cancer, normal VEGF concentrations (74.29 +/- 13.38 vs. 84.85 +/- 21.71 pg/mL; p > 0.05) and increased bFGF (29.52 +/- 4.99 vs. 6.05 +/- 1.43 pg/mL; p < 0.001), MMP-2 (605.95 +/- 81.83 vs. 148.75 +/- 43.53 ng/mL; p < 0.001), TIMP-2 (114.19 +/- 6.62 vs. 60.75 +/- 9.18 ng/mL; p < 0.001), as well as lower MMP-1 (0.70 +/- 0.42 vs. 3.87 +/- 0.53; p < 0.001) levels have been noted. Increased plasma levels of MMP-3 and MMP-9 were also found in patients with medullary carcinoma. In conclusion, predominance of MMP-2 over TIMP-2 and TIMP-1 over MMP-1 as well as increased concentration of bFGF in peripheral blood are common features in patients with thyroid cancer.

Adult↗