Novel cancerization marker, TP53, and its role in distinguishing normal tissue adjacent to cancerous tissue from normal tissue adjacent to benign tissue

Foundation of Xiamen Science and Technology Bureau [3502Z20104032, 3502Z20100002]; Medical innovation Foundation of Fujian Health Department [2011-CXB-38]; Natural Science Foundation of Fujian Province [2010J05137, 2012J01414]; National Natural Science Foundation of China [81272445, 61100106]Background: The histopathological and molecular heterogeneity of normal tissue adjacent to cancerous tissue (NTAC) and normal tissue adjacent to benign tissue (NTAB), and the availability of limited specimens make deciphering the mechanisms of carcinogenesis challenging. Our goal was to identify histogenetic biomarkers that could be reliably used to define a transforming fingerprint using RNA in situ hybridization. Methods: We evaluated 15 tumor-related RNA in situ hybridization biomarkers using tumor microarray and samples of seven tumor-adjacent normal tissues from 314 patients. Biomarkers were determined using comprehensive statistical methods (significance of support vector machine-based artificial intelligence and area under curve scoring of classification distribution). Results: TP53 was found to be a most reliable index (P 87%) for distinguishing NTAC from NTAB, according to the results of a significance panel (BCL10, BECN1, BRCA2, FITH, PTCH11 and TP53). Conclusions: The genetic alterations in TP53 between NTAC and NTAB may provide new insight into the field of cancerization and tumor transformation

Inhibition of Hypoxia-Inducible Factor-1α (HIF-1α) Protein Synthesis by DNA damage inducing agents

10.1371/journal.pone.0010522PLoS ONE55

Preparation and Characterization of a Lovastatin-Loaded Protein-Free Nanostructured Lipid Carrier Resembling High-Density Lipoprotein and Evaluation of its Targeting to Foam Cells

This study was designed to investigate whether a non-protein nanostructured lipid carrier (NLC) resembling high-density lipoprotein (HDL) could deliver a hydrophobic anti-atherogenic drug, lovastatin, to foam cells. Lovastatin-loaded NLC (LT-NLC) was prepared by a nanoprecipitation/solvent diffusion method. The LT-NLC-apoprotein (LT-NLC-apo) was prepared by incubating LT-NLC with native HDL. The physicochemical parameters of LT-NLC were characterized in terms of particle size, zeta potential, morphology, entrapment efficiency, and crystallization behavior. Targeting behavior and mechanism were demonstrated by the incubation of LT-NLC-apo with a RAW 264.7 macrophage-derived foam cell model in the presence or absence of very-low-density lipoprotein (VLDL) and lipase. The results showed that LT-NLC was solid spherical or oval in shape with an average diameter of 13.8 ± 2.2 nm, zeta potential of −29.3 ± 0.2 mV and entrapment efficiency of 96.2 ± 1.3%. Phagocytosis studies showed that uptake of LT-NLC-apo by macrophages was significantly lower than LT-NLC (p < 0.01), suggesting that LT-NLC-apo could possibly escape recognition from macrophages in vivo. The uptake was increased twofold when LT-NLC-apo was incubated with transfected foam cells containing VLDL and lipase. These results indicated that non-protein NLC resembling HDL could be a useful tool to deliver lipophilic anti-atherogenic drugs to foam cells, and that uptake could be enhanced by the VLDL receptor pathway

Genome-wide analysis in over 1 million individuals of European ancestry yields improved polygenic risk scores for blood pressure traits

Hypertension affects more than one billion people worldwide. Here we identify 113 novel loci, reporting a total of 2,103 independent genetic signals (P < 5 × 10−8) from the largest single-stage blood pressure (BP) genome-wide association study to date (n = 1,028,980 European individuals). These associations explain more than 60% of single nucleotide polymorphism-based BP heritability. Comparing top versus bottom deciles of polygenic risk scores (PRSs) reveals clinically meaningful differences in BP (16.9 mmHg systolic BP, 95% CI, 15.5–18.2 mmHg, P = 2.22 × 10−126) and more than a sevenfold higher odds of hypertension risk (odds ratio, 7.33; 95% CI, 5.54–9.70; P = 4.13 × 10−44) in an independent dataset. Adding PRS into hypertension-prediction models increased the area under the receiver operating characteristic curve (AUROC) from 0.791 (95% CI, 0.781–0.801) to 0.826 (95% CI, 0.817–0.836, ∆AUROC, 0.035, P = 1.98 × 10−34). We compare the 2,103 loci results in non-European ancestries and show significant PRS associations in a large African-American sample. Secondary analyses implicate 500 genes previously unreported for BP. Our study highlights the role of increasingly large genomic studies for precision health research

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis.

BACKGROUND: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. RESULTS: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. CONCLUSIONS: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk

Robust multiple time series modelling

A robust estimation procedure for multiple time series is proposed based on robustifying the residual autocovariances in the estimating equation. The asymptotic distribution of these estimators is derived. A robustified multivariate portmanteau statistic is also obtained which can be useful in model diagnostic checking. An illustrative example based on the mink-muskrat data is presented. © 1989 Biometrika Trust.link_to_subscribed_fulltex

Estimation of random coefficient autoregressive process: an empirical Bayes Approach

The problem of estimating panel autoregressive time series is considered. The autoregressive parameters vary over independent realizations from an unknown distribution. An empirical Bayes procedure is suggested to estimate the parameters using information from all realizations