Toxicogenomics scoring system: TGSS, a novel integrated risk assessment model for chemical carcinogenicity prediction.

BACKGROUND: Given the increasing exposure of humans to environmental chemicals and the limitations of conventional toxicity test, there is an urgent need to develop next-generation risk assessment methods. OBJECTIVES: This study aims to establish a novel computational system named Toxicogenomics Scoring System (TGSS) to predict the carcinogenicity of chemicals coupling chemical-gene interactions with multiple cancer transcriptomic datasets. METHODS: Chemical-related gene signatures were derived from chemical-gene interaction data from the Comparative Toxicogenomics Database (CTD). For each cancer type in TCGA, genes were ranked by their effects on tumorigenesis, which is based on the differential expression between tumor and normal samples. Next, we developed carcinogenicity scores (C-scores) using pre-ranked GSEA to quantify the correlation between chemical-related gene signatures and ranked gene lists. Then we established TGSS by systematically evaluating the C-scores in multiple chemical-tumor pairs. Furthermore, we examined the performance of our approach by ROC curves or prognostic analyses in TCGA and multiple independent cancer cohorts. RESULTS: Forty-six environmental chemicals were finally included in the study. C-score was calculated for each chemical-tumor pair. The C-scores of IARC Group 3 chemicals were significantly lower than those of chemicals in Group 1 (P-value = 0.02) and Group 2 (P-values = 7.49 ×10-5). ROC curves analysis indicated that C-score could distinguish "high-risk chemicals" from the other compounds (AUC = 0.67) with a specificity and sensitivity of 0.86 and 0.57. The results of survival analysis were also in line with the assessed carcinogenicity in TGSS for the chemicals in Group 1. Finally, consistent results were further validated in independent cancer cohorts. CONCLUSION: TGSS highlighted the great potential of integrating chemical-gene interactions with gene-cancer relationships to predict the carcinogenic risk of chemicals, which would be valuable for systems toxicology.

Assessment of vascular and endothelial function in Kawasaki disease.

BACKGROUND: Kawasaki disease (KD) is an acute febrile vasculitis. Patients with previous KD have increased risk of coronary arterial aneurysms (CAA) and early-onset arteriosclerosis. Endothelial dysfunction is the earliest manifestation of arteriosclerosis. We aimed to explore the endothelial function and clinical characteristics of patients with previous KD. METHODS: In this case-control study, we investigated childhood KD patients, with and without CAA, and a group of healthy controls. We obtained the anthropometric measurements, metabolic markers, vascular ultrasonography evaluating arterial stiffness and flow-mediated dilatation (FMD), and clinical information obtained by reviewing the patients' charts. Continuous variables were compared using non-parametric analyses and categorical variables, using the chi-square or Fisher's exact tests. RESULTS: Seventy KD patients (median current age, 12.95 years; median follow-up duration, 10.88 years) and 14 healthy controls were recruited. FMD was significantly lower in the CAA group (n = 15) than the control group (FMDs: 5.59% [interquartile range, 3.99-6.86%] vs. 7.49% [5.96-9.42%], p = 0.049; diastolic FMD: 6.48% [4.14-7.32%] vs. 7.87% [6.19-9.98%], p = 0.042). The CAA group had a higher percentage of impaired FMD and the significantly largest coronary segments of the three groups. Other parameters including metabolic markers, carotid intima-media thickness, and arterial stiffness were not statistically different. CONCLUSION: KD patients, especially those with CAAs, may have impaired endothelial function. FMD may be a good indicator of endothelial dysfunction for use in long-term follow-up of KD patients.

Phthalate pollution driven by the industrial plastics market: a case study of the plastic market in Yuyao City, China.

In attempts to evaluate the environmental risk produced by plastic markets, the levels and congener profiles of phthalate esters (PAEs) in soil, vegetable, and sediment samples collected from the plastic market in China, where numerous plastic products are exchanged every year, were investigated. The concentrations of ∑22PAEs ranged from 2131 to 27,805 ng g-1 in agricultural soils, from 8023 to 37,556 ng g-1 in vegetables and from 9031 to 87,329 ng g-1 in sediments. The predominant PAE pollutants were di-(2-ethylhexyl) phthalate (DEHP), di-n-butyl phthalate (DnBP), di-isobutyl phthalate (DiBP), and dibenzyl phthalate (DBzP). The mean percentages of the predominant PAEs in the soil, vegetable, and sediment samples accounted for 98.4%, 97.3%, and 99.5% of the total PAEs, respectively. The concentrations of PAEs at the sites around the plastic market were significantly higher than those at other pollution sites, such as sites contaminated by agricultural plastic film, electronic waste (e-waste) recycling sites, and industrial parks, indicating that the plastic market was an important pollution source. The DEHP concentrations in the soils, vegetables, and sediments and the DnBP concentrations in the vegetables all exceeded the environmental risk levels (ERL) or the environmental allowable levels (EAL), indicating that the plastic market posed potential environmental risks.

Cancer risk assessment of selected hazardous air pollutants in Seattle.

The risk estimates calculated from the conventional risk assessment method usually are compound specific and provide limited information for source-specific air quality control. We used a risk apportionment approach, which is a combination of receptor modeling and risk assessment, to estimate source-specific lifetime excess cancer risks of selected hazardous air pollutants. We analyzed the speciated PM(2.5) and VOCs data collected at the Beacon Hill in Seattle, WA between 2000 and 2004 with the Multilinear Engine to first quantify source contributions to the mixture of hazardous air pollutants (HAPs) in terms of mass concentrations. The cancer risk from exposure to each source was then calculated as the sum of all available species' cancer risks in the source feature. We also adopted the bootstrapping technique for the uncertainty analysis. The results showed that the overall cancer risk was 6.09 x 10(-5), with the background (1.61 x 10(-5)), diesel (9.82 x 10(-6)) and wood burning (9.45 x 10(-6)) sources being the primary risk sources. The PM(2.5) mass concentration contributed 20% of the total risk. The 5th percentile of the risk estimates of all sources other than marine and soil were higher than 110(-6). It was also found that the diesel and wood burning sources presented similar cancer risks although the diesel exhaust contributed less to the PM(2.5) mass concentration than the wood burning. This highlights the additional value from such a risk apportionment approach that could be utilized for prioritizing control strategies to reduce the highest population health risks from exposure to HAPs.