Common genetic polymorphisms modify the effect of smoking on absolute risk of bladder cancer

The Significant Associations between Epigenetic Clocks and Bladder Cancer Risks

Bladder cancer is an age-related disease, with over three-quarters of cases occurring in individuals aged 65 years and older. Accelerated biological aging has been linked to elevated cancer risks. Epigenetic clocks serve as excellent predictors of biological age, yet it remains unclear whether they are associated with bladder cancer risk. In this large case-control study, we assessed the associations between four well-established epigenetic clocks-HannumAge, HorvathAge, GrimAge, and PhenoAge-and bladder cancer risk. Utilizing single nucleotide polymorphisms (SNPs), which were identified in a genome-wide association study (GWAS), linked to these clocks as instruments, we constructed a weighted genetic risk score (GRS) for each clock. We discovered that higher HannumAge and HorvathAge GRS were significantly associated with increased bladder cancer risk (OR = 1.69 per SD increase, 95% CI, 1.44-1.98, p = 1.56 × 10-10 and OR = 1.09 per SD increase, 95% CI, 1.00-1.19, p = 0.04, respectively). Employing a summary statistics-based Mendelian randomization (MR) method, inverse-variance weighting (IVW), we found consistent risk estimates for bladder cancer with both HannumAge and HorvathAge. Sensitivity analyses using weighted median analysis and MR-Egger regression further supported the validity of the IVW method. However, GrimAge and PhenoAge were not associated with bladder cancer risk. In conclusion, our data provide the first evidence that accelerated biological aging is associated with elevated bladder cancer risk.

Effects of Eribulin on the RNA Content of Extracellular Vesicles Released by Metastatic Breast Cancer Cells

Extracellular vesicles (EVs) are small lipid particles secreted by almost all human cells into the extracellular space. They perform the essential function of cell-to-cell communication, and their role in promoting breast cancer progression has been well demonstrated. It is known that EVs released by triple-negative and highly aggressive MDA-MB-231 breast cancer cells treated with paclitaxel, a microtubule-targeting agent (MTA), promoted chemoresistance in EV-recipient cells. Here, we studied the RNA content of EVs produced by the same MDA-MB-231 breast cancer cells treated with another MTA, eribulin mesylate. In particular, we analyzed the expression of different RNA species, including mRNAs, lncRNAs, miRNAs, snoRNAs, piRNAs and tRNA fragments by RNA-seq. Then, we performed differential expression analysis, weighted gene co-expression network analysis (WGCNA), functional enrichment analysis, and miRNA-target identification. Our findings demonstrate the possible involvement of EVs from eribulin-treated cells in the spread of chemoresistance, prompting the design of strategies that selectively target tumor EVs.

Cigarette Smoking, Smoking Cessation, and Bladder Cancer Risk: A Pooled Analysis of 10 Cohort Studies in Japan

BACKGROUND

Although cigarette smoking is an established risk factor for bladder cancer, assessment of smoking impact on bladder cancer in Asian populations has been hindered by few cohort studies conducted in Asian populations. Therefore, we investigated the risk of bladder cancer associated with smoking status, cumulative smoking intensity, and smoking cessation in Japan.

METHODS

We analyzed data for 157,295 men and 183,202 women in 10 population-based cohort studies in Japan. The risk associated with smoking behaviors was estimated using Cox regression models within each study, and pooled hazard ratios (HRs) and their 95% confidence intervals (CIs) for the incidence of bladder cancer were calculated.

RESULTS

During 4,729,073 person-years of follow-up, 936 men and 325 women developed bladder cancer. In men, former smokers (HR 1.47; 95% CI, 1.18-1.82) and current smokers (HR 1.96; 95% CI, 1.62-2.38) had higher risk than never smokers. In women, current smokers had higher risk than never smokers (HR 2.35; 95% CI, 1.67-3.32). HRs in men linearly increased with increasing pack-years. Risk decreased with increasing years of smoking cessation in men, with a significant dose-response trend. Former smokers with a duration of more than 10 years after smoking cessation had no significantly increased risk compared with never smokers (HR 1.26; 95% CI, 0.97-1.63).

CONCLUSION

Data from a pooled analysis of 10 population-based cohort studies in Japan clearly show an association between cigarette smoking and bladder cancer risk. The risk of smokers may approximate that of never smokers following cessation for many years.

Familial Risk and Interaction With Smoking and Alcohol Consumption in Bladder Cancer: A Population-Based Cohort Study

Background

Although genetic factors are known to play a role in the pathogenesis of bladder cancer, population-level familial risk estimates are scarce. We aimed to quantify the familial risk of bladder cancer and analyze interactions between family history and smoking or alcohol consumption.

Methods

Using the National Health Insurance database, we constructed a cohort of 5,524,403 study subjects with first-degree relatives (FDRs) and their lifestyle risk factors from 2002 to 2019. Familial risk was calculated using hazard ratios (HRs) with 95% confidence intervals (CIs) that compare the risk of individuals with and without affected FDRs. Interactions between family history and smoking or alcohol intake were assessed on an additive scale using the relative excess risk due to interaction (RERI).

Results

Offspring with an affected parent had a 2.09-fold (95% CI: 1.41 - 3.08) increased risk of disease compared to those with unaffected parents. Familial risks of those with affected father and mother were 2.26 (95% CI: 1.51 - 3.39) and 1.10 (95% CI: 0.27 - 4.41), respectively. When adjusted for lifestyle factors, HR reduced slightly to 2.04 (95% CI: 1.38 - 3.01), suggesting that a genetic predisposition is the main driver in the familial aggregation. Smokers with a positive family history had a markedly increased risk of disease (HR: 3.60, 95% CI: 2.27 - 5.71), which exceeded the sum of their individual risks, with statistically significant interaction (RERI: 0.72, 95% CI: 0.31 - 1.13). For alcohol consumption, drinkers with a positive family history also had an increased risk of disease, although the interaction was not statistically significant (RERI: 0.05, 95% CI: -3.39 - 3.48).

Conclusion

Smokers and alcohol consumers with a positive family history of bladder cancer should be considered a high-risk group and be advised to undergo genetic counseling.

Survival and Enrichment Analysis of Epithelial-Mesenchymal Transition Genes in Bladder Urothelial Carcinoma

The escalating prevalence of bladder cancer, particularly urothelial carcinoma, necessitates innovative approaches for prognosis and therapy. This study delves into the significance of genes related to epithelial-mesenchymal transition (EMT), a process inherently linked to carcinogenesis and comparatively better studied in other cancers. We examined 1184 EMT-related gene expression levels in bladder urothelial cancer cases through the TCGA dataset. Genes shown to be differentially expressed in relation to survival underwent further network and enrichment analysis to uncover how they might shape disease outcomes. Our in silico analysis revealed a subset of 32 genes, including those significantly represented in biological pathways such as VEGF signaling and bacterium response. In addition, these genes interact with genes involved in the JAK-STAT signaling pathway. Additionally, some of those 32 genes have been linked to immunomodulators such as chemokines CCL15 and CCL18, as well as to various immune cell infiltrates. Our findings highlight the prognostic utility of various EMT-related genes and identify possible modulators of their effect on survival, allowing for further targeted wet lab research and possible therapeutic intervention.

A Case-Only Genome-Wide Interaction Study of Smoking and Bladder Cancer Risk: Results from the COBLAnCE Cohort

Bladder cancer (BC) is the 6th most common cancer worldwide, with tobacco smoking considered as its main risk factor. Accumulating evidence has found associations between genetic variants and the risk of BC. Candidate gene-environment interaction studies have suggested interactions between cigarette smoking and NAT2/GSTM1 gene variants. Our objective was to perform a genome-wide association case-only study using the French national prospective COBLAnCE cohort (COhort to study BLAdder CancEr), focusing on smoking behavior. The COBLAnCE cohort comprises 1800 BC patients enrolled between 2012 and 2018. Peripheral blood samples collected at enrolment were genotyped using the Illumina Global Screening Array with a Multi-Disease drop-in panel. Genotyping data (9,719,614 single nucleotide polymorphisms (SNP)) of 1674, 1283, and 1342 patients were analyzed for smoking status, average tobacco consumption, and age at smoking initiation, respectively. A genome-wide association study (GWAS) was conducted adjusting for gender, age, and genetic principal components. The results suggest new candidate loci (4q22.1, 12p13.1, 16p13.3) interacting with smoking behavior for the risk of BC. Our results need to be validated in other case-control or cohort studies.

Genome-wide Association Study of Bladder Cancer Reveals New Biological and Translational Insights

BACKGROUND

Genomic regions identified by genome-wide association studies (GWAS) for bladder cancer risk provide new insights into etiology.

OBJECTIVE

To identify new susceptibility variants for bladder cancer in a meta-analysis of new and existing genome-wide genotype data.

DESIGN, SETTING, AND PARTICIPANTS

Data from 32 studies that includes 13,790 bladder cancer cases and 343,502 controls of European ancestry were used for meta-analysis.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSES

Log-additive associations of genetic variants were assessed using logistic regression models. A fixed-effects model was used for meta-analysis of the results. Stratified analyses were conducted to evaluate effect modification by sex and smoking status. A polygenic risk score (PRS) was generated on the basis of known and novel susceptibility variants and tested for interaction with smoking.

RESULTS AND LIMITATIONS

Multiple novel bladder cancer susceptibility loci (6p.22.3, 7q36.3, 8q21.13, 9p21.3, 10q22.1, 19q13.33) as well as improved signals in three known regions (4p16.3, 5p15.33, 11p15.5) were identified, bringing the number of independent markers at genome-wide significance (p < 5 × 10-8) to 24. The 4p16.3 (FGFR3/TACC3) locus was associated with a stronger risk for women than for men (p-interaction = 0.002). Bladder cancer risk was increased by interactions between smoking status and genetic variants at 8p22 (NAT2; multiplicative p value for interaction [pM-I] = 0.004), 8q21.13 (PAG1; pM-I = 0.01), and 9p21.3 (LOC107987026/MTAP/CDKN2A; pM-I = 0.02). The PRS based on the 24 independent GWAS markers (odds ratio per standard deviation increase 1.49, 95% confidence interval 1.44-1.53), which also showed comparable results in two prospective cohorts (UK Biobank, PLCO trial), revealed an approximately fourfold difference in the lifetime risk of bladder cancer according to the PRS (e.g., 1st vs 10th decile) for both smokers and nonsmokers.

CONCLUSIONS

We report novel loci associated with risk of bladder cancer that provide clues to its biological underpinnings. Using 24 independent markers, we constructed a PRS to stratify lifetime risk. The PRS combined with smoking history, and other established risk factors, has the potential to inform future screening efforts for bladder cancer.

PATIENT SUMMARY

We identified new genetic markers that provide biological insights into the genetic causes of bladder cancer. These genetic risk factors combined with lifestyle risk factors, such as smoking, may inform future preventive and screening strategies for bladder cancer.

Polygenic Risk Prediction in Diverticulitis

OBJECTIVE

To derive and validate a polygenic risk score (PRS) to predict the occurrence and severity of diverticulitis and to understand the potential for incorporation of a PRS in current decision-making.

BACKGROUND

PRS quantifies genetic variation into a continuous measure of risk. There is a need for improved risk stratification to guide surgical decision-making that could be fulfilled by PRS. It is unknown how surgeons might integrate PRS in decision-making.

METHODS

We derived a PRS with 44 single-nucleotide polymorphisms associated with diverticular disease in the UK Biobank and validated this score in the Michigan Genomics Initiative (MGI). We performed a discrete choice experiment of practicing colorectal surgeons. Surgeons rated the influence of clinical factors and a hypothetical polygenic risk prediction tool.

RESULTS

Among 2812 MGI participants with diverticular disease, 1964 were asymptomatic, 574 had mild disease, and 274 had severe disease. PRS was associated with occurrence and severity. Patients in the highest PRS decile were more likely to have diverticulitis [odds ratio (OR)=1.84; 95% confidence interval (CI), 1.42-2.38)] and more likely to have severe diverticulitis (OR=1.61; 95% CI, 1.04-2.51) than the bottom 50%. Among 213 surveyed surgeons, extreme disease-specific factors had the largest utility (3 episodes in the last year, +74.4; percutaneous drain, + 69.4). Factors with strongest influence against surgery included 1 lifetime episode (-63.3), outpatient management (-54.9), and patient preference (-39.6). PRS was predicted to have high utility (+71).

CONCLUSIONS

A PRS derived from a large national biobank was externally validated, and found to be associated with the incidence and severity of diverticulitis. Surgeons have clear guidance at clinical extremes, but demonstrate equipoise in intermediate scenarios. Surgeons are receptive to PRS, which may be most useful in marginal clinical situations. Given the current lack of accurate prognostication in recurrent diverticulitis, PRS may provide a novel approach for improving patient counseling and decision-making.

Global burden of cancers attributable to tobacco smoking, 1990-2019: an ecological study

Aim and background

Identifying risk factors for cancer initiation and progression is the cornerstone of the preventive approach to cancer management and control (EPMA J. 4(1):6, 2013). Tobacco smoking is a well-recognized risk factor for initiation and spread of several cancers. The predictive, preventive, and personalized medicine (PPPM) approach to cancer management and control focuses on smoking cessation as an essential cancer prevention strategy. Towards this end, this study examines the temporal patterns of cancer burden due to tobacco smoking in the last three decades at global, regional, and national levels.

Data and methods

The data pertaining to the burden of 16 cancers attributable to tobacco smoking at global, regional, and national levels were procured from the Global Burden of Disease 2019 Study. Two main indicators, deaths and disability-adjusted life years (DALYs), were used to describe the burden of cancers attributable to tobacco smoking. The socio-economic development of countries was measured using the socio-demographic index (SDI).

Results

Globally, deaths due to neoplasms caused by tobacco smoking increased from 1.5 million in 1990 to 2.5 million in 2019, whereas the age-standardized mortality rate (ASMR) decreased from 39.8/100,000 to 30.6/100,000 and the age-standardized DALY rate (ASDALR) decreased from 948.9/100,000 to 677.3/100,000 between 1990 and 2019. Males accounted for approximately 80% of global deaths and DALYs in 2019. Populous regions of Asia and a few regions of Europe account for the largest absolute burden, whereas countries in Europe and America have the highest age-standardized rates of cancers due to tobacco smoking. In 8 out of 21 regions, there were more than 100,000 deaths due to cancers attributable to tobacco smoking led by East Asia, followed by Western Europe in 2019. The regions of Sub-Saharan Africa (except southern region) had one of the lowest absolute counts of deaths, DALYs, and age-standardized rates. In 2019, tracheal, bronchus, and lung (TBL), esophageal, stomach, colorectal, and pancreatic cancer were the top 5 neoplasms attributable to tobacco smoking, with different burdens in regions as per their development status. The ASMR and ASDALR of neoplasms due to tobacco smoking were positively correlated with SDI, with pairwise correlation coefficient of 0.55 and 0.52, respectively.

Conclusion

As a preventive tool, tobacco smoking cessation has the biggest potential among all risk factors for preventing millions of cancer deaths every year. Cancer burden due to tobacco smoking is found to be higher in males and is positively associated with socio-economic development of countries. As tobacco smoking begins mostly at younger ages and the epidemic is unfolding in several parts of the world, more accelerated efforts are required towards tobacco cessation and preventing youth from entering this addiction. The PPPM approach to medicine suggests that not only personalized and precision medicine must be provided to cancer patients afflicted by tobacco smoking but personalized and targeted preventive solutions must be provided to prevent initiation and progression of smoking.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-022-00308-y.

Diet quality, common genetic polymorphisms, and bladder cancer risk in a New England population-based study

PURPOSE

We examined the interaction between common genetic bladder cancer variants, diet quality, and bladder cancer risk in a population-based case-control study conducted in New England.

METHODS

At the time of enrollment, 806 bladder cancer cases and 974 controls provided a DNA sample and completed a diet history questionnaire. Diet quality was assessed using the 2010 Alternate Healthy Eating Index (AHEI-2010) score. Single nucleotide polymorphisms (SNPs) reported in genome-wide association studies to be associated with bladder cancer risk were combined into a polygenic risk score and also examined individually for interaction with the AHEI-2010. Adjusted odds ratios (OR) and 95% confidence intervals (CI) were calculated using logistic regression.

RESULTS

A 1-standard deviation increase in polygenic risk score was associated with higher bladder cancer risk (OR, 1.34; 95% CI 1.21-1.49). Adherence to the AHEI-2010 was not associated with bladder cancer risk (OR, 0.99; 95% CI 0.98-1.00) and the polygenic risk score did not appear to modify the association between the AHEI-2010 and bladder cancer risk. In single-SNP analyses, rs8102137 (bladder cancer risk allele, C) modified the association between the AHEI-2010 total score and bladder cancer risk, with the strongest evidence for the AHEI-2010 long chain fat guideline (OR for TT, 0.92; 95% CI 0.87-0.98; OR for CT, 1.02; 95% CI 0.96-1.08; OR for CC, 1.03; 95% CI 0.93-1.14; p for interaction, 0.02).

CONCLUSIONS

In conclusion, rs8102137 near the cyclin E1 gene ( CCNE1 ) may be involved in gene-diet interactions for bladder cancer risk.

Mechanism of Sex Differences in Bladder Cancer: Evident and Elusive Sex-biasing Factors

Bladder cancer incidence is drastically higher in males than females across geographical, racial, and socioeconomic strata. Despite potential differences in tumor biology, however, male and female bladder cancer patients are still clinically managed in highly similar ways. While sex hormones and sex chromosomes have been shown to promote observed sex differences, a more complex story lies beneath these evident sex-biasing factors than previously appreciated. Advances in genomic technology have spurred numerous preclinical studies characterizing elusive sex-biasing factors such as epigenetics, X chromosome inactivation escape genes, single nucleotide polymorphism, transcription regulation, metabolism, immunity, and many more. Sex-biasing effects, if properly understood, can be leveraged by future efforts in precision medicine based on a patient's biological sex. In this review, we will highlight key findings from the last half century that demystify the intricate ways in which sex-specific biology contribute to differences in pathogenesis as well as discuss future research directions.

The interaction between smoking and bladder cancer genetic variants on urothelial cancer risk by disease aggressiveness

Background

Smoking has shown interactions with bladder cancer (BC) genetic variants, especially N‐acetyltransferase‐2 (NAT2), a tobacco smoke metabolism gene, on BC risk. The interactions by disease aggressiveness are unknown.

Methods

We investigated the interaction between smoking and 18 single nucleotide polymorphisms (SNPs) for BC, individually and in a genetic risk score (GRS), on urothelial cancer (UC) risk including BC. We analysed data from 25,453 individuals with 520 incident UCs during follow‐up, 339 non‐aggressive (non‐fatal, non‐muscle invasive) and 163 aggressive (all other) UCs. Hazard ratios (HRs), absolute risks and additive and multiplicative interactions for two‐by‐two combinations of never/ever smoking with low/high genetic risk were calculated.

Results

Smoking and NAT2 rs1495741 interacted strongly, positively on aggressive UC on both the multiplicative (p = 0.004) and additive (p = 0.0002) scale, which was not observed for non‐aggressive UC (p_interactions ≥ 0.6). This manifested in a higher HR of aggressive UC by ever smoking for the slow acetylation NAT2 genotype (HR, 5.00 [95% confidence interval, 2.67–9.38]) than for intermediate/fast acetylation NAT2 (HR, 1.50 [0.83–2.71]), and in differences in absolute risks by smoking and NAT2 genotype. Smoking also interacted additively and positively with the GRS on any UC (p = 0.01) and non‐aggressive UC (p = 0.02), but not on aggressive UC (p = 0.1). Gene‐smoking interactions of lesser magnitude than for NAT2 were found for SNPs in APOBEC3A, SLC14A1 and MYNN.

Conclusions

This study suggests that smoking increases UC risk more than expected when combined with certain genetic risks. Individuals with the slow acetylation NAT2 variant might particularly benefit from smoking intervention to prevent lethal UC; however, replication in larger studies is needed.

Genetic variants in splicing factor genes and susceptibility to bladder cancer

BACKGROUND

Genome-wide association studies have demonstrated that genetic variants are closely related to tumorigenesis and progression of cancer. However, the correlation between genetic variants in splicing factor genes and bladder cancer susceptibility remains unclear.

METHOD

A case-control study with 580 cases of bladder cancer and 1,101 controls was conducted to explore the association of single-nucleotide polymorphisms (SNPs) in splicing factors with bladder cancer susceptibility by logistic regression models, and multiple testing errors were justified by the false discovery rate (FDR) method. Next, we used the Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) datasets to further analyze the differential expression of candidate genes.

RESULTS

We found that rs978416 G>A in RBFOX3 contributed to a reduced risk of bladder cancer [adjusted odds ratio (OR) = 0.72, 95% confidence internal (CI) = 0.62-0.84, P = 3.54 × 10^-5], especially in individuals who never smoked (P = 7.83 × 10^-5). Stratified analysis showed that the protective effect of rs978416 was more significant in the subgroup of low grade and non-muscle invasive bladder cancer. Furthermore, the RBFOX3 mRNA expression was decreased in bladder tumor tissues. However, the relatively high expression of RBFOX3 was related to a higher bladder cancer stage.

CONCLUSIONS

Our findings indicated that SNP rs978416 G>A in RBFOX3 may be related to bladder cancer predisposition in Chinese population and might serve as a novel biomarker for bladder cancer risk.

Impact of adiposity on risk of female gout among those genetically predisposed: sex-specific prospective cohort study findings over >32 years

OBJECTIVES

To evaluate the joint (combined) association of excess adiposity and genetic predisposition with the risk of incident female gout, and compare to their male counterparts; and determine the proportion attributable to body mass index (BMI) only, genetic risk score (GRS) only, and to their interaction.

METHODS

We prospectively investigated potential gene-BMI interactions in 18 244 women from the Nurses' Health Study and compared with 10 888 men from the Health Professionals Follow-Up Study. GRS for hyperuricaemia was derived from 114 common urate-associated single nucleotide polymorphisms.

RESULTS

Multivariable relative risk (RR) for female gout was 1.49 (95% CI 1.42 to 1.56) per 5 kg/m² increment of BMI and 1.43 (1.35 to 1.52) per SD increment in the GRS. For their joint association of BMI and GRS, RR was 2.18 (2.03 to 2.36), more than the sum of each individual factor, indicating significant interaction on an additive scale (p for interaction <0.001). The attributable proportions of joint effect for female gout were 42% (37% to 46%) to adiposity, 37% (32% to 42%) to genetic predisposition and 22% (16% to 28%) to their interaction. Additive interaction among men was smaller although still significant (p interaction 0.002, p for heterogeneity 0.04 between women and men), and attributable proportion of joint effect was 14% (6% to 22%).

CONCLUSIONS

While excess adiposity and genetic predisposition both are strongly associated with a higher risk of gout, the excess risk of both combined was higher than the sum of each, particularly among women.

A Robust Test for Additive Gene-Environment Interaction Under the Trend Effect of Genotype Using an Empirical Bayes-Type Shrinkage Estimator

Evaluating gene by environment (G × E) interaction under an additive risk model (i.e., additive interaction) has gained wider attention. Recently, statistical tests have been proposed for detecting additive interaction, utilizing an assumption on gene-environment (G-E) independence to boost power, that do not rely on restrictive genetic models such as dominant or recessive models. However, a major limitation of these methods is a sharp increase in type I error when this assumption is violated. Our goal was to develop a robust test for additive G × E interaction under the trend effect of genotype, applying an empirical Bayes-type shrinkage estimator of the relative excess risk due to interaction. The proposed method uses a set of constraints to impose the trend effect of genotype and builds an estimator that data-adaptively shrinks an estimator of relative excess risk due to interaction obtained under a general model for G-E dependence using a retrospective likelihood framework. Numerical study under varying levels of departures from G-E independence shows that the proposed method is robust against the violation of the independence assumption while providing an adequate balance between bias and efficiency compared with existing methods. We applied the proposed method to the genetic data of Alzheimer disease and lung cancer.

Associations of genetically predicted circulating insulin-like growth factor-1 and insulin-like growth factor binding protein-3 with bladder cancer risk

Insulin-like growth factors (IGF) play important roles in carcinogenesis. The associations of circulating IGF-1 and insulin-like growth factor-binding protein-3 (IGFBP-3) with the risks of bladder cancer remain unclear. In this large case control study of 2011 bladder cancer cases and 2369 heathy controls, we assessed the associations of circulating IGF-1 and IGFBP-3 with bladder cancer risks using a Mendelian randomization approach, which uses genetic variants as instruments to study causal relationship between risk factors and diseases. We first constructed a weighted genetic risk score (GRS) predictive of circulating IGF-1 and IGFBP-3 using 413 genome-wide association study-identified single nucleotide polymorphisms (SNPs) associated with IGF-1 and four SNPs with IGFBP-3, respectively. We found that higher GRS for IGF-1 was associated with a significantly reduced bladder cancer risk (odds ratio [OR] = 0.66 per SD increase, 95% confidence interval [CI], 0.54-0.82, p < 0.001). We then used a summary statistics-based MR method, inverse-variance weighting (IVW), and found a similar risk estimate (OR = 0.67 per SD increase, 95% CI = 0.54-0.83, p < 0.001). When we categorized individuals into high and low IGF-1 groups using the median GRS value in the controls, the high GRS group had a 21% reduced bladder cancer risk (OR = 0.79, 95% CI = 0.70-0.89) compared to the low GRS group. Genetically predicted circulating IGFBP-3 was not associated with bladder cancer risk. In conclusion, our data demonstrated for the first time a strong inverse relationship between circulating IGF-1 level and bladder cancer risk.

Mouse Model to Explore the Therapeutic Effect of Nano-Doxorubicin Drug Delivery System on Bladder Cancer

To study the therapeutic effect of nano-dosin-loaded drug system in mouse bladder cancer, a luciferase-labeled mouse bladder cancer cell line and a mouse bladder cancer model were constructed. In vivo imaging monitors tumor growth and uses a combination of photothermal, immune, and chemotherapy to treat the mouse model. With doxorubicin as an antitumor drug carrier, the drug loading, in vitro drug release, cytotoxicity and behavior in cells of mesoporous nano particle-targeted drug delivery system were studied. The cells were injected into the bladder through the urethra, and the mouse bladder cancer subcutaneous model was treated with gelatin-coated single-walled carbon nanotube-encapsulated mouse granulocytes-macrophage colony-stimulating factor and doxorubicin. In the process of using, the use of near-infrared light for irradiation, thereby achieving the combined effect of photothermal, immune and chemotherapy. The experimental results show that the prepared doxorubicin prodrug delivery system can enhance the targeted therapeutic effect and reduce the toxicity and side effects of the drug. Especially for those cancer cells or tissues with overexpression of folate receptors, it has a better therapeutic effect and provides reference for the treatment of subsequent bladder cancer.

Pan-cancer analysis demonstrates that integrating polygenic risk scores with modifiable risk factors improves risk prediction

Cancer risk is determined by a complex interplay of environmental and heritable factors. Polygenic risk scores (PRS) provide a personalized genetic susceptibility profile that may be leveraged for disease prediction. Using data from the UK Biobank (413,753 individuals; 22,755 incident cancer cases), we quantify the added predictive value of integrating cancer-specific PRS with family history and modifiable risk factors for 16 cancers. We show that incorporating PRS measurably improves prediction accuracy for most cancers, but the magnitude of this improvement varies substantially. We also demonstrate that stratifying on levels of PRS identifies significantly divergent 5-year risk trajectories after accounting for family history and modifiable risk factors. At the population level, the top 20% of the PRS distribution accounts for 4.0% to 30.3% of incident cancer cases, exceeding the impact of many lifestyle-related factors. In summary, this study illustrates the potential for improving cancer risk assessment by integrating genetic risk scores.

Blood pressure and bladder cancer risk in men by use of survival analysis and in interaction with NAT2 genotype, and by Mendelian randomization analysis

The association between blood pressure (BP) and bladder cancer (BC) risk remains unclear with confounding by smoking being of particular concern. We investigated the association between BP and BC risk among men using conventional survival-analysis, and by Mendelian Randomization (MR) analysis in an attempt to disconnect the association from smoking. We additionally investigated the interaction between BP and N-acetyltransferase-2 (NAT2) rs1495741, an established BC genetic risk variant, in the association. Populations consisting of 188,167 men with 502 incident BC's in the UK-biobank and 27,107 men with 928 incident BC's in two Swedish cohorts were used for the analysis. We found a positive association between systolic BP and BC risk in Cox-regression survival analysis in the Swedish cohorts, (hazard ratio [HR] per standard deviation [SD]: 1.14 [95% confidence interval 1.05-1.22]) and MR analysis (odds ratio per SD: 2-stage least-square regression, 7.70 [1.92-30.9]; inverse-variance weighted estimate, 3.43 [1.12-10.5]), and no associations in the UK-biobank (HR systolic BP: 0.93 [0.85-1.02]; MR OR: 1.24 [0.35-4.40] and 1.37 [0.43-4.37], respectively). BP levels were positively associated with muscle-invasive BC (MIBC) (HRs: systolic BP, 1.32 [1.09-1.59]; diastolic BP, 1.27 [1.04-1.55]), but not with non-muscle invasive BC, which could be analyzed in the Swedish cohorts only. There was no interaction between BP and NAT2 in relation to BC on the additive or multiplicative scale. These results suggest that BP might be related to BC, more particularly MIBC. There was no evidence to support interaction between BP and NAT2 in relation to BC in our study.

Impact of Gene-Environment Interactions on Cancer Development

Several epidemiological and experimental studies have demonstrated that many human diseases are not only caused by specific genetic and environmental factors but also by gene-environment interactions. Although it has been widely reported that genetic polymorphisms play a critical role in human susceptibility to cancer and other chronic disease conditions, many single nucleotide polymorphisms (SNPs) are caused by somatic mutations resulting from human exposure to environmental stressors. Scientific evidence suggests that the etiology of many chronic illnesses is caused by the joint effect between genetics and the environment. Research has also pointed out that the interactions of environmental factors with specific allelic variants highly modulate the susceptibility to diseases. Hence, many scientific discoveries on gene-environment interactions have elucidated the impact of their combined effect on the incidence and/or prevalence rate of human diseases. In this review, we provide an overview of the nature of gene-environment interactions, and discuss their role in human cancers, with special emphases on lung, colorectal, bladder, breast, ovarian, and prostate cancers.

Combined Utility of 25 Disease and Risk Factor Polygenic Risk Scores for Stratifying Risk of All-Cause Mortality

While genome-wide association studies have identified susceptibility variants for numerous traits, their combined utility for predicting broad measures of health, such as mortality, remains poorly understood. We used data from the UK Biobank to combine polygenic risk scores (PRS) for 13 diseases and 12 mortality risk factors into sex-specific composite PRS (cPRS). These cPRS were moderately associated with all-cause mortality in independent data within the UK Biobank: the estimated hazard ratios per standard deviation were 1.10 (95% confidence interval: 1.05, 1.16) and 1.15 (1.10, 1.19) for women and men, respectively. Differences in life expectancy between the top and bottom 5% of the cPRS were estimated to be 4.79 (1.76, 7.81) years and 6.75 (4.16, 9.35) years for women and men, respectively. These associations were substantially attenuated after adjusting for non-genetic mortality risk factors measured at study entry (i.e., middle age for most participants). The cPRS may be useful in counseling younger individuals at higher genetic risk of mortality on modification of non-genetic factors.

Polygenic approaches to detect gene-environment interactions when external information is unavailable

The exploration of 'gene-environment interactions' (G × E) is important for disease prediction and prevention. The scientific community usually uses external information to construct a genetic risk score (GRS), and then tests the interaction between this GRS and an environmental factor (E). However, external genome-wide association studies (GWAS) are not always available, especially for non-Caucasian ethnicity. Although GRS is an analysis tool to detect G × E in GWAS, its performance remains unclear when there is no external information. Our 'adaptive combination of Bayes factors method' (ADABF) can aggregate G × E signals and test the significance of G × E by a polygenic test. We here explore a powerful polygenic approach for G × E when external information is unavailable, by comparing our ADABF with the GRS based on marginal effects of SNPs (GRS-M) and GRS based on SNP × E interactions (GRS-I). ADABF is the most powerful method in the absence of SNP main effects, whereas GRS-M is generally the best test when single-nucleotide polymorphisms main effects exist. GRS-I is the least powerful test due to its data-splitting strategy. Furthermore, we apply these methods to Taiwan Biobank data. ADABF and GRS-M identified gene × alcohol and gene × smoking interactions on blood pressure (BP). BP-increasing alleles elevate more BP in drinkers (smokers) than in nondrinkers (nonsmokers). This work provides guidance to choose a polygenic approach to detect G × E when external information is unavailable.

Gene-environment interaction with smoking for increased non-muscle-invasive bladder cancer tumor size

Background

Urinary bladder cancer (UBC) is one of few cancers with an established gene-environment interaction (GxE) with smoking. However, it is unknown whether the interaction with tobacco use is present non-muscle invasive bladder cancer (NMIBC) and characteristics of prognostic relevance. We aimed to investigate if smoking status and/or smoking intensity interact with the effect of discovered variants on key NMIBC characteristics of tumor grade, stage, size, and patient age within the Bladder Cancer Prognosis Programme (BCPP) cohort.

Methods

Analyzed sample consisted of 546 NMIBC patients with valid smoking data from the BCPP. In a previous genome-wide association study (GWAS), we have identified 61 single nucleotide polymorphisms (SNPs) potentially associated with the NMIBC characteristics of tumor stage, grade, size, and patient age. In the current analysis, we have tested these SNPs for GxE with smoking.

Results

Out of 61 SNPs, 10 have showed suggestion (statistical significance level of P<0.05) for GxE with NMIBC tumor size rs35225990, rs188958632, rs180910528, rs74603364, rs187040828, rs144383242, rs117587674, rs113705641, rs2937268, and chromosome 14:38247577. All SNPs were located across loci of 1p31.3, 3p26.1, 6q14.1, 14q21.1, and 13q14.13. In addition, two of the tested polymorphisms were suggestive for interaction with smoking intensity (chromosome 14:38247577 and rs2937268).

Conclusions

Our study suggests interaction between genetic variance and smoking behavior for increased NMIBC tumor size at the time of diagnosis. Further replication is required to validate these findings.

Assessment of polygenic architecture and risk prediction based on common variants across fourteen cancers

Genome-wide association studies (GWAS) have led to the identification of hundreds of susceptibility loci across cancers, but the impact of further studies remains uncertain. Here we analyse summary-level data from GWAS of European ancestry across fourteen cancer sites to estimate the number of common susceptibility variants (polygenicity) and underlying effect-size distribution. All cancers show a high degree of polygenicity, involving at a minimum of thousands of loci. We project that sample sizes required to explain 80% of GWAS heritability vary from 60,000 cases for testicular to over 1,000,000 cases for lung cancer. The maximum relative risk achievable for subjects at the 99th risk percentile of underlying polygenic risk scores (PRS), compared to average risk, ranges from 12 for testicular to 2.5 for ovarian cancer. We show that PRS have potential for risk stratification for cancers of breast, colon and prostate, but less so for others because of modest heritability and lower incidence.

From GWAS to Function: Using Functional Genomics to Identify the Mechanisms Underlying Complex Diseases

Genome-wide association studies (GWAS) have successfully mapped thousands of loci associated with complex traits. These associations could reveal the molecular mechanisms altered in common complex diseases and result in the identification of novel drug targets. However, GWAS have also left a number of outstanding questions. In particular, the majority of disease-associated loci lie in non-coding regions of the genome and, even though they are thought to play a role in gene expression regulation, it is unclear which genes they regulate and in which cell types or physiological contexts this regulation occurs. This has hindered the translation of GWAS findings into clinical interventions. In this review we summarize how these challenges have been addressed over the last decade, with a particular focus on the integration of GWAS results with functional genomics datasets. Firstly, we investigate how the tissues and cell types involved in diseases can be identified using methods that test for enrichment of GWAS variants in genomic annotations. Secondly, we explore how to find the genes regulated by GWAS loci using methods that test for colocalization of GWAS signals with molecular phenotypes such as quantitative trait loci (QTLs). Finally, we highlight potential future research avenues such as integrating GWAS results with single-cell sequencing read-outs, designing functionally informed polygenic risk scores (PRS), and validating disease associated genes using genetic engineering. These tools will be crucial to identify new drug targets for common complex diseases.

The emerging landscape of germline variants in urothelial carcinoma: Implications for genetic testing

Urothelial carcinoma (UC) of the bladder and upper tract (ureter, renal pelvis) is one of the most frequently occurring malignancies. While the majority of UC are chemically induced by smoking, accumulating evidence from genetic studies have demonstrated a small, but consistent impact of heritable gene variants and family history of UC on the development of the disease. Beyond the established association between upper tract UC and germline mismatch DNA repair defects as a defining feature of Lynch syndrome, newer investigations focusing on moderate- and high-risk cancer-related gene variants in DNA damage repair and other signaling pathways are expanding our knowledge on the heritable genetic basis of UC, opening new avenues in the breadth of genetic testing and in clinical counseling of these patients. Overcoming existing challenges in the interpretation of uncertain findings and family cascade testing may help expand our testing approach and guidelines. Following the paradigm of other tumor types, such as breast and ovarian cancers, germline genetic testing, particularly when combined with somatic testing, has the potential to directly benefit affected UC patients and their families in the future through therapeutic targeting (i.e. with poly(ADP-ribose)) polymerase inhibitors, immune checkpoint inhibitors) and genetically informed screening/surveillance, respectively.

Case-Only Analysis of Gene-Environment Interactions Using Polygenic Risk Scores

Investigations of gene (G)-environment (E) interactions have led to limited findings to date, possibly due to weak effects of individual genetic variants. Polygenic risk scores (PRS), which capture the genetic susceptibility associated with a set of variants, can be a powerful tool for detecting global patterns of interaction. Motivated by the case-only method for evaluating interactions with a single variant, we propose a case-only method for the analysis of interactions with a PRS in case-control studies. Assuming the PRS and E are independent, we show how a linear regression of the PRS on E in a sample of cases can be used to efficiently estimate the interaction parameter. Furthermore, if an estimate of the mean of the PRS in the underlying population is available, the proposed method can estimate the PRS main effect. Extensions allow for PRS-E dependence due to associations between variants in the PRS and E. Simulation studies indicate the proposed method offers appreciable gains in efficiency over logistic regression and can recover much of the efficiency of a cohort study. We applied the proposed method to investigate interactions between a PRS and epidemiologic factors on breast cancer risk in the UK Biobank (United Kingdom, recruited 2006-2010).

Moral reasons to edit the human genome: picking up from the Nuffield report

In July 2018, the Nuffield Council of Bioethics released its long-awaited report on heritable genome editing (HGE). The Nuffield report was notable for finding that HGE could be morally permissible, even in cases of human enhancement. In this paper, we summarise the findings of the Nuffield Council report, critically examine the guiding principles they endorse and suggest ways in which the guiding principles could be strengthened. While we support the approach taken by the Nuffield Council, we argue that detailed consideration of the moral implications of genome editing yields much stronger conclusions than they draw. Rather than being merely 'morally permissible', many instances of genome editing will be moral imperatives.

A comprehensive gene-environment interaction analysis in Ovarian Cancer using genome-wide significant common variants

As a follow-up to genome-wide association analysis of common variants associated with ovarian carcinoma (cancer), our study considers seven well-known ovarian cancer risk factors and their interactions with 28 genome-wide significant common genetic variants. The interaction analyses were based on data from 9971 ovarian cancer cases and 15,566 controls from 17 case-control studies. Likelihood ratio and Wald tests for multiplicative interaction and for relative excess risk due to additive interaction were used. The top multiplicative interaction was noted between oral contraceptive pill (OCP) use (ever vs. never) and rs13255292 (p value = 3.48 × 10-4 ). Among women with the TT genotype for this variant, the odds ratio for OCP use was 0.53 (95% CI = 0.46-0.60) compared to 0.71 (95%CI = 0.66-0.77) for women with the CC genotype. When stratified by duration of OCP use, women with 1-5 years of OCP use exhibited differential protective benefit across genotypes. However, no interaction on either the multiplicative or additive scale was found to be statistically significant after multiple testing correction. The results suggest that OCP use may offer increased benefit for women who are carriers of the T allele in rs13255292. On the other hand, for women carrying the C allele in this variant, longer (5+ years) use of OCP may reduce the impact of carrying the risk allele of this SNP. Replication of this finding is needed. The study presents a comprehensive analytic framework for conducting gene-environment analysis in ovarian cancer.

Systematic evaluation of cancer-specific genetic risk score for 11 types of cancer in The Cancer Genome Atlas and Electronic Medical Records and Genomics cohorts

BACKGROUND

Genetic risk score (GRS) is an odds ratio (OR)-weighted and population-standardized method for measuring cumulative effect of multiple risk-associated single nucleotide polymorphisms (SNPs). We hypothesize that GRS is a valid tool for risk assessment of most common cancers.

METHODS

Utilizing genotype and phenotype data from The Cancer Genome Atlas (TCGA) and Electronic Medical Records and Genomics (eMERGE), we tested 11 cancer-specific GRSs (bladder, breast, colorectal, glioma, lung, melanoma, ovarian, pancreatic, prostate, renal, and thyroid cancer) for association with the respective cancer type. Cancer-specific GRSs were calculated, for the first time in these cohorts, based on previously published risk-associated SNPs using the Caucasian subjects in these two cohorts.

RESULTS

Mean cancer-specific GRS in the population controls of eMERGE approximated the expected value of 1.00 (between 0.98 and 1.02) for all 11 types of cancer. Mean cancer-specific GRS was consistently higher in respective cancer patients than controls for all 11 types of cancer (P < 0.05). When subjects were categorized into low-, average-, and high-risk groups based on cancer-specific GRS (<0.5, 0.5-1.5, and >1.5, respectively), significant dose-response associations of higher cancer-specific GRS with higher OR of respective type of cancer were found for nine types of cancer (P_-trend  < 0.05). More than 64% subjects in the population controls of eMERGE can be classified as high risk for at least one type of these cancers.

CONCLUSION

Validity of GRS for predicting cancer risk is demonstrated for most types of cancer. If confirmed in larger studies, cancer-specific GRS may have the potential for developing personalized cancer screening strategy.

The UDP-Glycosyltransferase (UGT) Superfamily: New Members, New Functions, and Novel Paradigms

UDP-glycosyltransferases (UGTs) catalyze the covalent addition of sugars to a broad range of lipophilic molecules. This biotransformation plays a critical role in elimination of a broad range of exogenous chemicals and by-products of endogenous metabolism, and also controls the levels and distribution of many endogenous signaling molecules. In mammals, the superfamily comprises four families: UGT1, UGT2, UGT3, and UGT8. UGT1 and UGT2 enzymes have important roles in pharmacology and toxicology including contributing to interindividual differences in drug disposition as well as to cancer risk. These UGTs are highly expressed in organs of detoxification (e.g., liver, kidney, intestine) and can be induced by pathways that sense demand for detoxification and for modulation of endobiotic signaling molecules. The functions of the UGT3 and UGT8 family enzymes have only been characterized relatively recently; these enzymes show different UDP-sugar preferences to that of UGT1 and UGT2 enzymes, and to date, their contributions to drug metabolism appear to be relatively minor. This review summarizes and provides critical analysis of the current state of research into all four families of UGT enzymes. Key areas discussed include the roles of UGTs in drug metabolism, cancer risk, and regulation of signaling, as well as the transcriptional and posttranscriptional control of UGT expression and function. The latter part of this review provides an in-depth analysis of the known and predicted functions of UGT3 and UGT8 enzymes, focused on their likely roles in modulation of levels of endogenous signaling pathways.

Epidemiology of Bladder Cancer: A Systematic Review and Contemporary Update of Risk Factors in 2018

CONTEXT

Bladder cancer (BC) is a significant health problem, and understanding the risk factors for this disease could improve prevention and early detection.

OBJECTIVE

To provide a systematic review and summary of novel developments in epidemiology and risk factors for BC.

EVIDENCE ACQUISITION

A systematic review of original articles was performed by two pairs of reviewers (M.G.C., I.J., F.E., and K.P.) using PubMed/Medline in December 2017, updated in April 2018. To address our primary objective of reporting contemporary studies, we restricted our search to include studies from the last 5yr. We subdivided our review according to specific risk factors (PICO [Population Intervention Comparator Outcome]).

EVIDENCE SYNTHESIS

Our search found 2191 articles, of which 279 full-text manuscripts were included. We separated our manuscripts by the specific risk factor they addressed (PICO). According to GLOBOCAN estimates, there were 430000 new BC cases and 165000 deaths worldwide in 2012. Tobacco smoking and occupational exposure to carcinogens remain the factors with the highest attributable risk. The literature was limited by heterogeneity of data.

CONCLUSIONS

Evidence is emerging regarding gene-environment interactions, particularly for tobacco and occupational exposures. In some populations, incidence rates are declining, which may reflect a decrease in smoking. Standardisation of reporting may help improve epidemiologic evaluation of risk.

PATIENT SUMMARY

Bladder cancer is common worldwide, and the main risk factors are tobacco smoking and exposure to certain chemicals in the working and general environments. There is ongoing research to identify and reduce risk factors, as well as to understand the impact of genetics on bladder cancer risk.

From Single Level Analysis to Multi-Omics Integrative Approaches: A Powerful Strategy towards the Precision Oncology

Integration of multi-omics data from different molecular levels with clinical data, as well as epidemiologic risk factors, represents an accurate and promising methodology to understand the complexity of biological systems of human diseases, including cancer. By the extensive use of novel technologic platforms, a large number of multidimensional data can be derived from analysis of health and disease systems. Comprehensive analysis of multi-omics data in an integrated framework, which includes cumulative effects in the context of biological pathways, is therefore eagerly awaited. This strategy could allow the identification of pathway-addiction of cancer cells that may be amenable to therapeutic intervention. However, translation into clinical settings requires an optimized integration of omics data with clinical vision to fully exploit precision cancer medicine. We will discuss the available technical approach and more recent developments in the specific field.

Association of Polygenic Risk Scores for Multiple Cancers in a Phenome-wide Study: Results from The Michigan Genomics Initiative

Health systems are stewards of patient electronic health record (EHR) data with extraordinarily rich depth and breadth, reflecting thousands of diagnoses and exposures. Measures of genomic variation integrated with EHRs offer a potential strategy to accurately stratify patients for risk profiling and discover new relationships between diagnoses and genomes. The objective of this study was to evaluate whether polygenic risk scores (PRS) for common cancers are associated with multiple phenotypes in a phenome-wide association study (PheWAS) conducted in 28,260 unrelated, genotyped patients of recent European ancestry who consented to participate in the Michigan Genomics Initiative, a longitudinal biorepository effort within Michigan Medicine. PRS for 12 cancer traits were calculated using summary statistics from the NHGRI-EBI catalog. A total of 1,711 synthetic case-control studies was used for PheWAS analyses. There were 13,490 (47.7%) patients with at least one cancer diagnosis in this study sample. PRS exhibited strong association for several cancer traits they were designed for, including female breast cancer, prostate cancer, melanoma, basal cell carcinoma, squamous cell carcinoma, and thyroid cancer. Phenome-wide significant associations were observed between PRS and many non-cancer diagnoses. To differentiate PRS associations driven by the primary trait from associations arising through shared genetic risk profiles, the idea of "exclusion PRS PheWAS" was introduced. Further analysis of temporal order of the diagnoses improved our understanding of these secondary associations. This comprehensive PheWAS used PRS instead of a single variant.

Robust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence

There have been recent proposals advocating the use of additive gene-environment interaction instead of the widely used multiplicative scale, as a more relevant public health measure. Using gene-environment independence enhances statistical power for testing multiplicative interaction in case-control studies. However, under departure from this assumption, substantial bias in the estimates and inflated type I error in the corresponding tests can occur. In this paper, we extend the empirical Bayes (EB) approach previously developed for multiplicative interaction, which trades off between bias and efficiency in a data-adaptive way, to the additive scale. An EB estimator of the relative excess risk due to interaction is derived, and the corresponding Wald test is proposed with a general regression setting under a retrospective likelihood framework. We study the impact of gene-environment association on the resultant test with case-control data. Our simulation studies suggest that the EB approach uses the gene-environment independence assumption in a data-adaptive way and provides a gain in power compared with the standard logistic regression analysis and better control of type I error when compared with the analysis assuming gene-environment independence. We illustrate the methods with data from the Ovarian Cancer Association Consortium.

Identification and replication of the interplay of four genetic high-risk variants for urinary bladder cancer

Little is known whether genetic variants identified in genome-wide association studies interact to increase bladder cancer risk. Recently, we identified two- and three-variant combinations associated with a particular increase of bladder cancer risk in a urinary bladder cancer case-control series (Leibniz Research Centre for Working Environment and Human Factors at TU Dortmund (IfADo), 1501 cases, 1565 controls). In an independent case-control series (Nijmegen Bladder Cancer Study, NBCS, 1468 cases, 1720 controls) we confirmed these two- and three-variant combinations. Pooled analysis of the two studies as discovery group (IfADo-NBCS) resulted in sufficient statistical power to test up to four-variant combinations by a logistic regression approach. The New England and Spanish Bladder Cancer Studies (2080 cases and 2167 controls) were used as a replication series. Twelve previously identified risk variants were considered. The strongest four-variant combination was obtained in never smokers. The combination of rs1014971[AA] near apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3A (APOBEC3A) and chromobox homolog 6 (CBX6), solute carrier family 1s4 (urea transporter), member 1 (Kidd blood group) (SLC14A1) exon single nucleotide polymorphism (SNP) rs1058396[AG, GG], UDP glucuronosyltransferase 1 family, polypeptide A complex locus (UGT1A) intron SNP rs11892031[AA] and rs8102137[CC, CT] near cyclin E1 (CCNE1) resulted in an unadjusted odds ratio (OR) of 2.59 (95% CI = 1.93-3.47; P = 1.87 × 10-10), while the individual variant ORs ranged only between 1.11 and 1.30. The combination replicated in the New England and Spanish Bladder Cancer Studies (ORunadjusted = 1.60, 95% CI = 1.10-2.33; P = 0.013). The four-variant combination is relatively frequent, with 25% in never smoking cases and 11% in never smoking controls (total study group: 19% cases, 14% controls). In conclusion, we show that four high-risk variants can statistically interact to confer increased bladder cancer risk particularly in never smokers.

The awareness of patients with non - muscle invasive bladder cancer regarding the importance of smoking cessation and their access to smoking cessation programs

Objectives

Smoking is the most important risk factor for bladder cancer and smoking cessation is associated with reduced risk of tumor recurrence and progression. The aim of this study is to assess the awareness of non-muscle invasive bladder cancer (NMIBC) patients regarding the importance of smoking cessation, determine their access to smoking cessation programs and the effects of smoking cessation on recurrence rates of NMIBC.

Materials and Methods

NMIBC patients who were followed with cystoscopy were included in the study. Their demographic properties were recorded, along with their smoking habits, awareness regarding the effects of smoking on bladder cancer and previous attempts for smoking cessation. Moreover, the patients were asked whether they applied for a smoking cessation program. Recurrence of bladder cancer during the follow-up period was also noted.

Results

A total of 187 patients were included in the study. The mean age was 64.68±12.05 (range: 15-90) and the male to female ratio was 167/20. At the time of diagnosis, 114 patients (61.0%) were active smokers, 35 patients (18.7%) were ex-smokers and 38 patients (20.3%) had never smoked before. After the diagnosis, 83.3% of the actively smoking patients were advised to quit smoking and 57.9% of them quit smoking. At the time of the study, 46.52% of the NMIBC patients were aware of the link between smoking and bladder cancer, whereas only 4.1% of the smoking patients were referred to smoking cessation programs. After a mean follow-up of 32.28±11.42 months, 84 patients (44.91%) had recurrence; however, current smoking status or awareness of the causative role of smoking on NMIBC did not affect the recurrence.

Conclusion

In our study group, the majority of the NMIBC patients were not aware of the association between smoking and bladder cancer. Although most of the physicians advised patients to quit smoking, a significant amount of the patients were still active smokers during follow-up. Only a small proportion of patients were referred to smoking cessation programs. Urologists should take a more active role in the battle against smoking and refer those patients to smoking cessation programs. Larger study populations with longer follow-up periods are needed to better demonstrate the beneficial effects of smoking cessation on recurrence rates.

Genome-wide association studies of cancer: current insights and future perspectives

Genome-wide association studies (GWAS) provide an agnostic approach for investigating the genetic basis of complex diseases. In oncology, GWAS of nearly all common malignancies have been performed, and over 450 genetic variants associated with increased risks have been identified. As well as revealing novel pathways important in carcinogenesis, these studies have shown that common genetic variation contributes substantially to the heritable risk of many common cancers. The clinical application of GWAS is starting to provide opportunities for drug discovery and repositioning as well as for cancer prevention. However, deciphering the functional and biological basis of associations is challenging and is in part a barrier to fully unlocking the potential of GWAS.

Lessons Learned From Past Gene-Environment Interaction Successes

Genetic and environmental factors are both known to contribute to susceptibility to complex diseases. Therefore, the study of gene-environment interaction (G×E) has been a focus of research for several years. In this article, select examples of G×E from the literature are described to highlight different approaches and underlying principles related to the success of these studies. These examples can be broadly categorized as studies of single metabolism genes, genes in complex metabolism pathways, ranges of exposure levels, functional approaches and model systems, and pharmacogenomics. Some studies illustrated the success of studying exposure metabolism for which candidate genes can be identified. Moreover, some G×E successes depended on the availability of high-quality exposure assessment and longitudinal measures, study populations with a wide range of exposure levels, and the inclusion of ethnically and geographically diverse populations. In several examples, large population sizes were required to detect G×Es. Other examples illustrated the impact of accurately defining scale of the interactions (i.e., additive or multiplicative). Last, model systems and functional approaches provided insights into G×E in several examples. Future studies may benefit from these lessons learned.

Current Challenges and New Opportunities for Gene-Environment Interaction Studies of Complex Diseases

Recently, many new approaches, study designs, and statistical and analytical methods have emerged for studying gene-environment interactions (G×Es) in large-scale studies of human populations. There are opportunities in this field, particularly with respect to the incorporation of -omics and next-generation sequencing data and continual improvement in measures of environmental exposures implicated in complex disease outcomes. In a workshop called "Current Challenges and New Opportunities for Gene-Environment Interaction Studies of Complex Diseases," held October 17-18, 2014, by the National Institute of Environmental Health Sciences and the National Cancer Institute in conjunction with the annual American Society of Human Genetics meeting, participants explored new approaches and tools that have been developed in recent years for G×E discovery. This paper highlights current and critical issues and themes in G×E research that need additional consideration, including the improved data analytical methods, environmental exposure assessment, and incorporation of functional data and annotations.

Update on the State of the Science for Analytical Methods for Gene-Environment Interactions

The analysis of gene-environment interaction (G×E) may hold the key for further understanding the etiology of many complex traits. The current availability of high-volume genetic data, the wide range in types of environmental data that can be measured, and the formation of consortiums of multiple studies provide new opportunities to identify G×E but also new analytical challenges. In this article, we summarize several statistical approaches that can be used to test for G×E in a genome-wide association study. These include traditional models of G×E in a case-control or quantitative trait study as well as alternative approaches that can provide substantially greater power. The latest methods for analyzing G×E with gene sets and with data in a consortium setting are summarized, as are issues that arise due to the complexity of environmental data. We provide some speculation on why detecting G×E in a genome-wide association study has thus far been difficult. We conclude with a description of software programs that can be used to implement most of the methods described in the paper.

Long non-coding RNA HNF1A-AS1 promotes proliferation and suppresses apoptosis of bladder cancer cells through upregulating Bcl-2

Emerging evidences have indicated that long non-coding RNAs (lncRNAs) are pivotal regulators of tumor development and progression. HNF1A-AS1 (HNF1A antisense RNA 1, C12 or f27) is a novel long non-coding RNA that acts as a potential biomarker and is involved in development and progression of several cancers. Nevertheless, we know nothing about the clinical significance and molecular mechanism of HNF1A-AS1 in bladder cancer. In this study, we found that HNF1A-AS1 is significantly up-regulated in bladder cancer. Further experiments had demonstrated that silencing HNF1A-AS1 in bladder cancer cells could inhibit the proliferation and induce apoptosis. Mechanistically, we found down-regulated of HNF1A-AS1 increased the expression of miR-30b-5p and subsequently inhibited the expression of Bcl-2, in a ceRNA-dependent way. Moreover, knockdown of miR-30b-5p reversed cell proliferation inhibition and cell apoptosis induced by silencing HNF1A-AS1. In conclusions, we demonstrated that HNF1A-AS1 plays an important regulatory role in bladder cancer and shed new light on lncRNA-directed diagnostic and therapeutics in bladder cancer.

Impact of vascular endothelial growth factor gene-gene and gene-smoking interaction and haplotype combination on bladder cancer risk in Chinese population

AIMS

To investigate the association of single nucleotide polymorphisms (SNPs) within vascular endothelial growth factor (VEGF) gene polymorphisms, additional gene- gene and gene- smoking interactions with bladder cancer risk.

RESULTS

Bladder cancer risk was significantly higher in carriers of the rs699947- A allele within VEGF gene than those with rs699947- CC genotype (CA+ AA versus CC), adjusted OR (95%CI) = 1.70 (1.16-2.31), and higher in carriers of the rs833052- A allele of within VEGF gene than those with rs833052- CC genotype (CA+ AA versus CC), adjusted OR (95%CI) = 1.65 (1.23-2.12). GMDR analysis indicated a potential interaction between rs2010963 and smoking on bladder cancer risk. Current smokers with rs2010963- GC+CC genotype within VEGF gene have the highest bladder cancer risk, compared to never smokers with rs2010963- GG genotype within VEGF gene, OR (95%CI) = 3.25 (1.71-4.83). Haplotype containing the rs2010963- C and rs833052- A alleles were associated with a statistically increased bladder cancer risk, OR (95%CI) = 2.21 (1.12-3.42).

MATERIALS AND METHODS

Generalized multifactor dimensionality reduction (GMDR) was used to screen the best interaction combination among SNPs and smoking. Logistic regression was performed to investigate association of 6 SNPs within VEGF gene, additional gene- gene and gene- smoking interaction with bladder cancer risk.

CONCLUSIONS

We found that the A allele of rs699947 and the A allele of rs833052 within VEGF gene, interaction between rs2010963 and smoking, haplotype containing the rs2010963- C and rs833052- A alleles were all associated with increased bladder cancer risk.