DNA methylation-mediated low expression of ZNF582 promotes the proliferation, migration, and invasion of clear cell renal cell carcinoma.

OBJECTIVE: The methylation of DNA promoter region mediates the low expression of many tumor suppressor genes and plays an essential part in cancer progression. We investigated methylation and expression of ZNF582 in clear cell renal cell carcinoma (ccRCC), and to study the function of ZNF582 in ccRCC cells. METHODS: Methylation data and mRNA expression data of TCGA-KIRC were obtained from TCGA database to screen methylation-driven genes. Survival analysis and gene set enrichment analysis (GSEA) were done for the target gene. The methylation degree and mRNA level of ZNF582 in ccRCC cell line were detected by methylation-specific PCR (MSP) and qRT-PCR, respectively. Effects of overexpression of ZNF582 on ccRCC cells were assessed via CCK-8, flow cytometry, wound healing, Transwell, and cell adhesion assays. RESULTS: Eighteen methylation-driven genes were identified via bioinformatics methods. Among them, ZNF582 was noticeably hypermethylated and lowly expressed in tumor tissue, and ZNF582 methylation and expression levels were pronouncedly associated with prognosis and clinical stage. MSP also displayed that the ZNF582 DNA promoter region was hypermethylated in ccRCC cells, and the mRNA expression of ZNF582 was dramatically elevated after demethylation. In vitro cell experiments disclosed that overexpression of ZNF582 markedly hindered cell proliferation, invasion, migration, and fostered cell apoptosis and adhesion of ccRCC. CONCLUSION: ZNF582 was hypermethylated in ccRCC, which mediated its low level. Overexpression of ZNF582 inhibited tumor cell proliferation, migration and invasion. This study generates novel ideas for ccRCC diagnosis and treatment.

Performance Analysis of GNSS/INS Loosely Coupled Integration Systems under Spoofing Attacks.

The loosely coupled integration of Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS) have been widely used to improve the accuracy, robustness and continuity of navigation services. However, the integration systems possibly affected by spoofing attacks, since integration algorithms without spoofing detection would feed autonomous INSs with incorrect compensations from the spoofed GNSSs. This paper theoretically analyzes and tests the performances of GNSS/INS loosely coupled integration systems with the classical position fusion and position/velocity fusion under typical meaconing (MEAC) and lift-of-aligned (LOA) spoofing attacks. Results show that the compensations of Inertial Measurement Unit (IMU) errors significantly increase under spoofing attacks. The compensations refer to the physical features of IMUs and their unreasonable increments likely result from the spoofing-induced inconsistency of INS and GNSS measurements. Specially, under MEAC attacks, the IMU error compensations in both the position-fusion-based system and position/velocity-fusion-based system increase obviously. Under LOA attacks, the unreasonable compensation increments are found from the position/velocity-fusion-based integration system. Then a detection method based on IMU error compensations is tested and the results show that, for the position/velocity-fusion-based integration system, it can detect both MEAC and LOA attacks with high probability using the IMU error compensations.

A 9-gene prognostic signature for kidney renal clear cell carcinoma overall survival based on co-expression and regression analyses.

This research attempted to screen potential signatures associated with KIRC progression and overall survival by weighted gene co-expression network analysis (WGCNA) and Cox regression. The KIRC-associated mRNA expression and clinical data were accessed from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) were screened by differential analysis. A co-expression network was constructed by "WGCNA". Based on WGCNA module, GO and KEGG analyses were performed. Protein-protein interaction (PPI) network was constructed. Prognostic signatures were screened by Lasso-Cox regression. Prognostic model was evaluated by Receiver Operating Characteristic (ROC) and Kaplan-Meier (K-M) curves. Multivariate Cox and nomogram were introduced to examine whether risk score could be an independent marker. qRT-PCR was introduced to determine expression of 9 hub genes in KIRC clinical tumor tissues and adjacent tissues, respectively. Genes in the green module were highly associated with clinical status, and green module genes were significantly enriched in mitotic nuclear division, cell cycle, and p53 signaling pathway. Twenty-six candidates were subsequently screened out from the green module. Next, a 9-gene prognostic model (DLGAP5, NUF2, TOP2A, RRM2, HJURP, PLK1, AURKB, KIF18A, CCNB2) was constructed. The predicting ability of the model was optimal. Some cancer-related signaling pathways were differently activated between two risk score groups. Additionally, under-expression of some signature genes (AURKB, CCNB2, PLK1, RRM2, TOP2A) was associated with better survival rate for KIRC patients. Meanwhile, all 9 hub genes were substantially overexpressed in KIRC patients. A KIRC prognostic signature was screened in this study, contributing valuable findings to KIRC biomarker development.

Effect of AGER on the biological behavior of non­small cell lung cancer H1299 cells.

Advanced glycosylation end-product specific receptor (AGER) is a multi-ligand cell surface receptor abnormally expressed in lung cancer, and is a member of the immunoglobulin superfamily. Therefore, this study aimed to explore the effect of AGER on the biological behavior of non­small cell lung cancer (NSCLC) H1299 cell line. A microarray­based gene expression profiling analysis of the GSE27262 dataset from the Gene Expression Omnibus (GEO) database was conducted to identify differentially expressed genes, which were verified using The Cancer Genome Atlas (TCGA) database. The expression of AGER in the normal human lung BEAS­2B cell line and NSCLC H1299 cell line was examined using reverse transcription­quantitative PCR. Lentiviral interference and overexpression vectors of AGER were constructed and transfected into H1299 cells using Lipofectamine®. AGER expression and biological properties, including cell viability, apoptosis, migration and invasion abilities, in H1299 cells were investigated using MTT, flow cytometry, wound healing and Transwell assays. AGER was expressed at a low level in NSCLC tissues and H1299 cells (P<0.05). Compared with control cells, AGER overexpression cells displayed decreased cell viability, proliferation, migration and invasion abilities, and significantly increased levels of apoptosis. Furthermore, AGER overexpression increased the expression of Bax and decreased the expression of Bcl­2 in H1299 cells (P<0.05), and AGER knockdown displayed the opposite effects on H1299 cells. Therefore, AGER overexpression decreased the proliferation, invasion and migration abilities of H1299 cells, and increased apoptosis. The present study suggested that AGER might serve as a potential molecular marker for NSCLC.

Contribution of phthalates and phthalate monoesters from drinking water to daily intakes for the general population.

Although phthalates (PAEs) are ubiquitous in drinking water, and phthalate monoesters (MPAEs) have been recognized as the bioactive metabolites of PAEs, little information is available regarding the occurrence of MPAEs in drinking water and the contributions of PAEs and MPAEs to human exposure. In this study, the concentrations of PAEs and MPAEs in 146 samples of drinking water collected from 24 cities throughout China were determined. The mean concentrations of dimethyl phthalate (DMP), diethyl phthalate (DEP), diisobutyl phthalate (DiBP), di-n-butyl phthalate (DnBP), and di-2-ethylhexyl phthalate (DEHP) were 14.31 ±â€¯26.28, 5.905 ±â€¯11.57, 103.8 ±â€¯310.5, 595.9 ±â€¯1794, and 178.2 ±â€¯422.0 ng/L, respectively. Monomethyl phthalate (MMP), monoethyl phthalate (MEP), monoisobutyl phthalate (MiBP), mono-n-butyl phthalate (MnBP), and mono-2-ethylhexyl phthalate (MEHP) were detected in drinking water for the first time, at mean concentrations of 12.1 ±â€¯18.0, 2.4 ±â€¯5.8, 11.3 ±â€¯37.2, 36.3 ±â€¯103, and 9.9 ±â€¯18.0 ng/L, respectively. The geometric mean concentrations of MMP, MEP, MiBP, MnBP, and MEHP in urine samples collected from 1040 participants from 16 cities were 10.1, 19.3, 29.6, 47.3, and 3.63 µg/g creatinine, respectively. The concentrations of PAEs and MPAEs in drinking water and daily intakes (DIs) of PAEs from nine cities where drinking water and urine samples were simultaneously collected were used to estimate the contributions from drinking water. The percentages of DMP, DEP, DiBP, DnBP, and DEHP from drinking water accounted for DIs of 0.60%, 0.049%, 1.26%, 2.76%, and 0.56%, respectively. The percentages of MMP, MEP, MiBP, MnBP and MEHP via intake of drinking water accounted for urinary concentrations of 0.86%, 0.032%, 0.14%, 0.089%, and 0.045%, respectively.

Relationship between perfluorooctanoate and perfluorooctane sulfonate blood concentrations in the general population and routine drinking water exposure.

In regions with heavily contaminated drinking water, a significant contribution of drinking water to overall human perfluorooctane sulfonate (PFOS) and perfluorooctanoate (PFOA) exposure has been well documented. However, the relationship of PFOA/PFOS blood concentrations in the general population to routine drinking water exposure is not well characterized. This study determined the PFOA and PFOS concentrations in 166 drinking water samples across 28 cities in China. For 13 of the studied cities, PFOA and PFOS concentrations were analyzed in 847 human blood samples which were collected in parallel with the drinking water samples. The geometric mean PFOA and PFOS concentrations in drinking water were 2.5 ±â€¯6.2 ng/L and 0.7 ±â€¯11.7 ng/L, and population-weighted geometric mean blood concentrations were 2.1 ±â€¯1.2 ng/mL and 2.6 ±â€¯1.3 ng/mL, respectively. We found a significant correlation between the PFOA concentration in drinking water and blood (r = 0.87, n = 13, p < 0.001). The total daily intake of PFOA (0.24-2.13 ng/kg/day) and PFOS (0.19-1.87 ng/kg/day) were back-calculated from the blood concentrations with a one-compartment toxicokinetic model. We estimated relative source contributions (RSCs) of drinking water to total daily intake in China of 23 ±â€¯3% for PFOA and 12.7 ±â€¯5.8% for PFOS. Using the mean RSCs, we derived the health advisory values of 85 ng/L for PFOA and 47 ng/L for PFOS in China.

Simultaneous determination of primary and secondary phthalate monoesters in the Taihu Lake: Exploration of sources.

While phthalates monoesters have been recognized as the bioactive metabolites of phthalates, the knowledge on their environmental occurrence and sources is limited. In this study, monomethyl phthalate (MMP), monoethyl phthalate (MEP), mono-iso-butyl phthalate (MiBP), mono-n-butyl phthalate (MnBP), and mono-2-ethylhexyl phthalate (MEHP) were frequently detected in water samples from the Taihu Lake in China using an improved SPE-LC-MS-MS method. The mean concentrations for MMP, MEP, MiBP, MnBP, and MEHP were 51.7 ±â€¯25.2, 6.0 ±â€¯4.8, 19.6 ±â€¯14.6, 42.2 ±â€¯64.7, and 33.0 ±â€¯37.4 ng/L, respectively, while those of their corresponding parent chemicals, DMP, DEP, DiBP, and DnBP and DEHP, were 36.54 ±â€¯43.22, 42.64 ±â€¯66.66, 246.8 ±â€¯311.1, 524.7 ±â€¯586.9, and 208.1 ±â€¯223.5 ng/L, respectively. Three secondary monoesters of DEHP, mono (2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), mono (2-ethyl-5-oxohexyl) phthalate (MEOHP), and mono (2-ethyl-5-carboxypentyl) phthalate (MECPP) were for the first time detected with mean concentration of 1.27 ±â€¯1.33, 1.33 ±â€¯1.54, and 0.73 ±â€¯0.79 ng/L, respectively. The percentage of the sum concentration of MEOHP, MEHHP, and MECPP relative to total concentration of DEHP metabolites was 5.3-12.4%. DEHP was identified to be biodegraded into secondary phthalate monoesters in water from the Taihu Lake, but their contribution to the total concentration of DEHP metabolites was 1.2-3.6%, lower than those in the Taihu Lake. Primary and secondary DEHP monoesters were also detected in influents and effluents of two sewage treatment plants adjacent to the Taihu Lake, the percentages of secondary DEHP monoesters in influents were 5.8% and 11.3%, similar with those in the Taihu Lake. Taken together with their relatively high concentrations in influents, the discharging of domestic wastewater may be an important contributor to the occurrence of phthalate monoesters in the Taihu Lake.