It is widely hypothesized that the interactions of multiple genes influence individual risk to prostate cancer. However, current efforts at identifying prostate cancer risk genes primarily rely on single-gene approaches. In an attempt to fill this gap, we carried out a study to explore the joint effect of multiple genes in the inflammation pathway on prostate cancer risk. We studied 20 genes in the Toll-like receptor signaling pathway as well as several cytokines. For each of these genes, we selected and genotyped haplotype-tagging single nucleotide polymorphisms (SNP) among 1,383 cases and 780 controls from the CAPS (CAncer Prostate in Sweden) study population. A total of 57 SNPs were included in the final analysis. A data mining method, multifactor dimensionality reduction, was used to explore the interaction effects of SNPs on prostate cancer risk. Interaction effects were assessed for all possible n SNP combinations, where n = 2, 3, or 4. For each n SNP combination, the model providing lowest prediction error among 100 cross-validations was chosen. The statistical significance levels of the best models in each n SNP combination were determined using permutation tests. A four-SNP interaction (one SNP each from IL-10, IL-1RN, TIRAP, and TLR5) had the lowest prediction error (43.28%, P = 0.019). Our ability to analyze a large number of SNPs in a large sample size is one of the first efforts in exploring the effect of high-order gene-gene interactions on prostate cancer risk, and this is an important contribution to this new and quickly evolving field. (Cancer Epidemiol Biomarkers Prev 2005;14(11):2563 -8)
Mesenchymal stem cells (MSCs) and their derived extracellular vesicles have been reported as promising tools for the management of heart disease. The aim of this study was to explore the function of adipose-derived MSCs (adMSCs)-derived exosomes (Exo) in the progression of myocardial infarction (MI) and the molecules involved. Mouse cardiomyocytes were treated with oxygen-glucose deprivation (OGD) to mimic an MI condition in vitro. The adMSCs-derived Exo were identified and administrated into the OGD-treated cardiomyocytes, and then the viability and apoptosis of cells, and the secretion of fibrosis- and inflammation-related cytokines in cells were determined. Differentially expressed microRNAs (miRNAs) in cells after Exo treatment were screened using a microarray analysis. The downstream molecules regulated by miR-671 were explored through bioinformatic analysis. Involvements of miR-671 and transforming growth factor beta receptor 2 (TGFBR2) in the exosome-mediated events were confirmed by rescue experiments. A murine model with MI was induced and treated with Exo for functional experiments in vivo. Compared to phosphate-buffered saline treatment, the Exo treatment significantly enhanced viability while reduced apoptosis of cardiomyocytes, and in reduced myocardial fibrosis and inflammation both in vitro and in vivo. miR-671 was significantly upregulated in cells after Exo treatment. Downregulation of miR-671 blocked the protective functions of Exo. miR-671 targeted TGFBR2 and suppressed phosphorylation of Smad2. Artificial downregulation of TGFBR2 enhanced viability of the OGD-treated cardiomyocytes. This study suggested that adMSC-derived exosomal miR-671 directly targets TGFBR2 and reduces Smad2 phosphorylation to alleviate MI-like symptoms both in vivo and in vitro.
BackgroundReperfusion injury is one of the leading causes of myocardial cell death and heart failure. This study was performed to identify new candidate lipid biomarkers for the purpose of optimizing the diagnosis of myocardial ischemia reperfusion (I/R) injury, assessing the severity of myocardial I/R injury and trying to find the novel mechanism related to lipids.Material/MethodsForty patients who were diagnosed with ST-segment elevation myocardial infarction (STEMI) were randomly selected for this study. Serum samples from all the patients with STEMI were collected at 3 time periods: after STEMI diagnosis but prior to reperfusion (T0); and then at 2 hours (T2) and 24 hours (T24) after the end of the percutaneous coronary intervention procedure. Plasma lipidomics profiling analysis was performed to identify the lipid metabolic signatures of myocardial I/R injury using lipidomics.ResultsSixteen types of potential lipid biomarkers at different time periods (T0, T2, T24) were identified by using lipidomics technology. The T0 time periods exhibited 16 differentially metabolized lipid peaks in the patients after STEMI diagnosis but prior to reperfusion. With the increase of reperfusion times, the contents of these 16 lipid biomarkers decreased gradually, but there was a 1.5- to 2-fold increase of those 16 lipid biomarkers contents at T2 compared with T24.ConclusionsLipidomics analysis demonstrated differential change before and after reperfusion, suggesting a potential role of some of these lipids as biomarkers for optimizing the diagnosis of myocardial I/R, as well as for therapeutic targets against myocardial I/R injury.
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