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A recent genome-wide association study identified two common variants that confer susceptibility to bladder cancer. We hypothesized that these variants are associated with risk of bladder cancer in Chinese populations. We genotyped rs9642880 G>T on 8q24 and rs710521 A>G on 3q28 in a two-stage case–control study of bladder cancer to evaluate the association and further examined the expression of MYC. We found that the rs9642880 G>T, but not the rs710521 A>G polymorphism, was associated with an increased risk of bladder cancer. Compared with the rs9642880 GG genotype, the GT/TT genotypes were associated with an odds ratio of 1.65 (95% confidence interval = 1.25–2.17), and this risk was more pronounced in young men and for low-risk tumors. Additional experiments revealed that the rs9642880 GT/TT genotypes were associated with enhanced levels of both MYC mRNA and protein in bladder tissues. Our findings suggested that the rs9642880 G>T polymorphism on 8q24 was independently associated with the risk of bladder cancer in Chinese populations. [ABSTRACT FROM AUTHOR]

FAS is a cell surface receptor involved in apoptotic signal transmission and plays important roles in the etiology of cancer. The −1377G>A and −670A>G polymorphisms of the FAS gene influence the FAS transcription and have been implicated in cancer risk. However, the results from the published studies on the association between these two FAS polymorphisms and cancer risk are conflicting. To derive a more precise estimation of association between the FAS polymorphisms and risk of cancer, we performed a meta-analysis of 11 461 cancer cases and 12 708 controls from 34 published case–control studies for these two polymorphisms. We used odds ratios (ORs) with 95% confidence intervals (CIs) to assess the strength of the association. Overall, individuals with the −1377AA genotype were associated with higher cancer risk than those with the −1377GG (OR = 1.21, 95% CI: 1.08–1.36, Pheterogeneity = 0.062) or GA/GG (OR = 1.23, 95% CI: 1.10–1.36, Pheterogeneity = 0.060) genotypes, whereas the −670GG genotype had no effects on overall cancer risk. In the stratified analyses for the −1377G>A polymorphism, there was a significantly increased risk of breast cancer but a significantly decreased risk of melanoma in a dominant model. Moreover, a significantly increased risk was observed among smokers in a recessive model (OR = 1.96, 95% CI: 1.55–2.49; Pheterogeneity = 0.528). Although some modest bias could not be eliminated, this meta-analysis suggested that the FAS −1377A allele is a low-penetrant risk factor for cancer development, particularly among smokers. [ABSTRACT FROM AUTHOR]

Transforming growth factor-β (TGF-β) is a multifunctional growth factor that plays important roles in many biological processes, whereas RUNX3 is a target of TGF-β-mediated tumor suppressor pathway. In humans, RUNX3 inactivation may lead to the cancer development, including bladder cancer. To determine whether the RUNX3 polymorphisms are associated with risk of bladder cancer, we conducted a case–control study of 368 bladder cancer patients and 368 cancer-free controls to assess the associations between the RUNX3 tagging single-nucleotide polymorphisms (tSNPs) and bladder cancer risk. In the single-locus analysis, we found a significantly increased risk of bladder cancer associated with the SNP7 rs760805 AA genotype (adjusted odds ratio = 1.97, 95% confidence interval = 1.44–2.69), compared with the AT/TT genotype. Haplotype-based association analysis revealed that the increased risk of bladder cancer was significantly associated with two haplotypes TATCCCAAAA (2.37, 1.16–4.83) and AGCTTGAGAG (2.70, 1.08–6.72) that included the rs760805 A allele. Multifactor dimensionality reduction (MDR) analysis identified a significant more than multiplicative interaction between the SNP7 rs760805 AA and smoking and an additive interaction between the SNP3 rs11249206 TT and smoking on bladder cancer risk. The SNP3 rs11249206, SNP5 rs1395621, SNP7 rs760805, SNP8 rs2236852 and the trichotomized cumulative smoking were the five factors best predicted by the MDR models. When the variables were combined and dichotomized and fitted into the MDR model, the subjects carrying the combined risk stratum had a significantly increased risk for bladder cancer (6.37, 4.57–8.87, P = 7.03 × 10−28). These results suggested that the genetic variants in RUNX3 may modulate the risk of bladder cancer. [ABSTRACT FROM AUTHOR]

The Hedgehog signaling pathway participates in the occurrence and progression of cancers including gastric cancer. We conducted this study to evaluate whether genetic variants in the Hedgehog signaling pathway genes would affect gastric cancer risk. Multi-marker Analysis of GenoMic Annotation (MAGMA) was used to investigate the aggregated genetic effects of single nucleotide polymorphisms (SNPs) assigned to candidate genes. The relationship between SNPs and gastric cancer risk was estimated by multivariate logistic regression analyses. Gene expression was calculated using databases obtained from The Cancer Genome Atlas (TCGA) and The Gene Expression Omnibus (GEO). Kaplan-Meier plotter was used to evaluate the association between gene expression with gastric cancer survival. Tumor Immune Estimation Resource 2.0 (TIMER 2.0) was applied to determine the correlation between selected gene expression and the immune cell infiltration degree. We identified that the G allele of rs2990912 in KIF27 was associated with higher gastric cancer risk, especially in the young and male subgroups. The expression of KIF27 in gastric cancer tissues was higher than that in normal tissues, leading to poor survival in gastric cancer patients. Besides, KIF27 expression was related to immune cell infiltration and positively correlated with PD-L1 expression. Our findings highlight the key role of genetic variation in the Hedgehog signaling pathway genes in gastric cancer susceptibility, which may provide important insights into the diagnosis, prognosis, and treatment of gastric cancer. [ABSTRACT FROM AUTHOR]

Lung cancer ranks first in both incidence and mortality and is a major health concern worldwide. Upon recognition of specific antigens on tumor cells, complement-dependent cytotoxicity (CDC) is activated, arresting cell growth or inducing apoptosis. However, by overexpressing CD59, a membrane complement regulatory protein (mCRP), lung cancer cells develop resistance to CDC. We previously showed that virus-like particles (VLPs) of human JC polyomavirus (JCPyV) could be used as a gene therapy vector to carry a suicide gene expression plasmid with a lung-specific promoter (SP-B (surfactant protein B)) for lung adenocarcinomas. Herein, we designed a CD59-specific short hairpin RNA (shRNA) expression plasmid driven by SP-B (pSPB-shCD59) to effectively and specifically inhibit CD59 overexpression in lung cancer cells. Treatment of lung cancer cells in vitro with JCPyV VLPs containing pSPB-shCD59 (pSPB-shCD59/VLPs) induces CDC and death of cancer cells. Mice that were subcutaneously injected with human lung cancer cells showed an 87% inhibition in tumor growth after tail vein injection of pSPB-shCD59/VLPs. Moreover, in a mouse model of lung cancer metastasis, a reduction in the lung weight by 39%, compared with the control group, was observed in mice treated with pSPB-shCD59/VLPs after tail vein injection of human lung cancer cells. Furthermore, tissue sectioning showed that the number and size of tumors produced was significantly reduced in the lungs of mice in the treatment group than those of the untreated group, indicating inhibition of metastasis by pSPB-shCD59/VLPs. Together, these results demonstrate the potential of pSPB-shCD59/VLPs as a therapeutic agent for CD59 overexpressed lung cancer. [ABSTRACT FROM AUTHOR]

The switching defective/sucrose nonfermenting (SWI/SNF) related, matrix associated, actin dependent regulators of chromatin (SMARC) are components of human SWI/SNF like chromatin remodeling protein complexes, which are essential in the process of DNA damage repair. In this study, we hypothesized that genetic variants in SMARC genes may modify the capacity of DNA repair to damage. To test this hypothesis, we genotyped a total of 20 polymorphisms in five key SMARC genes (SMARCA5, SMARCC2, SMARCD1, SMARCD2, SMARCD3) to evaluate their associations with DNA damage levels in 307 subjects. The DNA damage levels were measured with comet assay. The multiple linear regression was used to assess the relationship between each polymorphism and DNA damage levels in additive model. We found that the genotypes of rs6857360 (β = 0.23, 95% CI = 0.06-0.40, P = 0.008) in SMARCA5, rs6919 (β = 0.20, 95% CI = 0.05-0.34, P = 0.008) and rs2727280 (β = 0.18, 95% CI = 0.04-0.33, P = 0.013) in SMARCD2, and rs17173769 (β = -0.27, 95% CI = -0.52 to -0.01, P = 0.045) in SMARCD3 were significantly associated with DNA damage levels. After combining these four polymorphisms, we found that the more unfavorable alleles the subjects carried, the heavier DNA damage they suffered, suggesting a locus-dosage effect between combined genotypes and DNA damage levels (P for trend = 0.006). These findings suggest that genetic variants in SMARC genes may contribute the individual variations of DNA damage levels in Chinese population. Further larger and functional studies are warranted to confirm our findings. [ABSTRACT FROM AUTHOR]

• Twelve machine learning algorithms are compared to construct a retrieval model. • The TN concentration is retrieved using the UAV Hyper Spectral Remote Sensing data. • Spatial distribution of TN concentration is retrieved with high resolution. • Providing scientific references for water quality monitoring and management. Monitoring the water pollution level in real time is the most critical issue for protecting the water quality of water reservoirs. Due to the restrictions on flight areas of Unmanned Arial Vehicles (UAV), four sensitive regions with the area of 1–2 km2 were first selected in this study based on the spatial distribution of total nitrogen (TN) concentration changes estimated by the Landsat remote sensing data. And then twelve machine learning algorithms including Support Vector Machine (SVM), Artificial Neural Networks (ANN), Bayesian Ridge Regression (BRR), Lasso Regression (Lasso), Elastic Net (EN), Linear Regression (LR), Decision Tree Regression (DTR), K Neighbors Regression (KNR), Random Forest Regression (RFR), Extra Trees Regression (ETR), AdaBoost Regression (ABR) and Gradient Boosting Regression (GBR) were compared to construct a more accurate retrieval model by using the UAV hyper spectral remote sensing and ground monitoring data. And then the TN concentration was estimated after the process of dimensionality reduction and compressed sensing denoing. Finally, spatial heterogeneity of the TN concentration was analyzed in four sensitive areas of the Miyun reservoir. The results demonstrated that among the tested algorithms the Extra Trees Regression was best suitable for the construction of a TN concentration retrieval model on the basis of UAV hyper spectral data, and its absolute squared error was 0.000065. The spatial distribution of the TN showed that the concentration was highest within the water area of the Bulaotun village and the Houbajiazhuang village, while it was relatively low for the Chao river dam and Bai river dam. Additionally, no significant differences regarding the concentrations were shown in the single UAV flight area except the Houbajia village, which indicated that the water quality in Miyun reservoir was relatively stable and changed in a small interval. These conclusions can provide scientific references for water quality monitoring and management in the water reservoir. [ABSTRACT FROM AUTHOR]