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Purpose To examine differences between genders in exposure to psychosocial and ergonomic factors at work and in work-related health, according to different work organization models. Methods The study population included a sample of 9749 (women: 37.1%) and 10,374 (women: 39.9%) employees who participated in the 2010 and 2015 European Working Conditions Surveys, respectively. Multiple Correspondence Analysis was applied to work characteristics reported by workers to estimate principal components, followed by Hierarchical Clustering on principal components to identify clusters of work organization models. Gender differences in exposure to work hazards and health outcomes were assessed through Poisson robust regression. Differences of PRs across organizational models were tested through interaction between gender and type of work organization. Results Three organizational models were identified in 2010, including lean production, Tayloristic production, and a “reflexive production” model, whereas in 2015, a “simple” or traditional model was also found. In 2010, women employed in companies adopting the Tayloristic or the lean production models were more likely than men to be exposed to unfavourable psychosocial and physical work factors, and to report musculoskeletal pain, compared to those belonging to reflexive production. In 2015, a significantly higher female/male ratio persisted in lean production for exposure to high job strain and for carrying/moving heavy loads, whereas gender differences in Tayloristic and traditional production were quite similar to those of reflexive production. Conclusions Our results suggest that employment in workplaces characterized by lower monotony, repetitiveness, and production constraints may contribute to reduce exposure to job strain among working women.

Background: Testicular germ cell tumors (TGCT), histologically classified as seminomas and nonseminomas, are believed to arise from primordial gonocytes, with the maturation process blocked when they are subjected to DNA methylation reprogramming. SNPs in DNA methylation machinery and folate-dependent one-carbon metabolism genes have been postulated to influence the proper establishment of DNA methylation. Methods: In this pathway-focused investigation, we evaluated the association between 273 selected tag SNPs from 28 DNA methylation–related genes and TGCT risk. We carried out association analysis at individual SNP and gene-based level using summary statistics from the Genome Wide Association Study meta-analysis recently conducted by the international Testicular Cancer Consortium on 10,156 TGCT cases and 179,683 controls. Results: In individual SNP analyses, seven SNPs, four mapping within MTHFR, were associated with TGCT risk after correction for multiple testing (q ≤ 0.05). Queries of public databases showed that three of these SNPs were associated with MTHFR changes in enzymatic activity (rs1801133) or expression level in testis tissue (rs12121543, rs1476413). Gene-based analyses revealed MTHFR (q = 8.4 × 10–4), methyl-CpG–binding protein 2 (MECP2; q = 2 × 10–3), and ZBTB4 (q = 0.03) as the top TGCT-associated genes. Stratifying by tumor histology, four MTHFR SNPs were associated with seminoma. In gene-based analysis MTHFR was associated with risk of seminoma (q = 2.8 × 10–4), but not with nonseminomatous tumors (q = 0.22). Conclusions: Genetic variants within MTHFR, potentially having an impact on the DNA methylation pattern, are associated with TGCT risk. Impact: This finding suggests that TGCT pathogenesis could be associated with the folate cycle status, and this relation could be partly due to hereditary factors.

Background: Many studies have shown that socioeconomic position (SEP) is associated with the incidence of malignant tumors at different sites. This study aims to estimate the association between educational level (as proxy for SEP) and cancer incidence and to understand whether the observed associations might be partially explained by lifestyle behaviors. Methods: The analyses were performed on data from the European Prospective Investigation into Cancer and Nutrition (EPIC) study, globally and by sex. We used Cox proportional hazards models together with mediation analysis to disentangle the total effect (TE) of educational level [measured through the Relative Index of Inequality (RII)] on cancer incidence into pure direct (PDE) and total indirect (TIE) effect, unexplained and explained by mediators, respectively. PDE and TIE were then combined to compute the proportions mediated (PM). Results: After an average of 14 years of follow-up, 52,422 malignant tumors were ascertained. Low educated participants showed higher risk of developing stomach, lung, kidney (in women), and bladder (in men) cancers, and, conversely, lower risk of melanoma and breast cancer (in post-menopausal women), when compared with more educated participants. Mediation analyses showed that portions of the TE of RII on cancer could be explained by site-specific related lifestyle behaviors for stomach, lung, and breast (in women). Conclusions: Cancer incidence in Europe is determined at least in part by a socioeconomically stratified distribution of risk factors. Impact: These observational findings support policies to reduce cancer occurrence by altering mediators, such as lifestyle behaviors, particularly focusing on underprivileged strata of the population.

Summary Background In many European countries, human papillomavirus (HPV) vaccine uptake among girls has remained below target levels, supporting the scope for vaccination of boys. We aimed to investigate if sex-neutral HPV vaccination can be considered cost-effective compared with girls-only vaccination at uptake levels equal to those among girls and under tender-based vaccination costs achieved throughout Europe. Methods We investigated the cost-effectiveness of sex-neutral HPV vaccination in European tender-based settings. We applied a Bayesian synthesis framework for health economic evaluation to 11 countries (Austria, Belgium, Croatia, Estonia, Italy, Latvia, the Netherlands, Poland, Slovenia, Spain, and Sweden), accommodating country-specific information on key epidemiological and economic parameters, and on current HPV vaccination programmes. We used projections from three independently developed HPV transmission models to tailor region-specific herd effects. The main outcome measures in the comparison of sex-neutral with girls-only vaccination were cancer cases prevented and incremental cost-effectiveness ratios (ICERs), defined as the cost in international dollars (I$) per life-year gained. Findings The total number of cancer cases to be prevented by vaccinating girls at currently realised vaccine uptake varied from 318 (95% CI 197–405) per cohort of 200 000 preadolescents (100 000 girls plus 100 000 boys) in Croatia (under 20% uptake of the 9-valent vaccine) to 1904 (1741–2101) in Estonia (under 70% uptake of the 9-valent vaccine). Vaccinating boys at equal coverage increased these respective numbers by 168 (95% CI 121–213) in Croatia and 467 (391–587) in Estonia. Sex-neutral vaccination was likely to be cost-effective, with ICERs of sex-neutral compared with girls-only vaccination varying from I$4300 per life-year gained in Latvia (95% credibility interval 3450–5160; 40% uptake) to I$25 720 per life-year gained in Spain (21 380–30 330; 80% uptake). At uniform 80% uptake, a favourable cost-effectiveness profile was retained for most of the countries investigated (Austria, Belgium, Italy, Latvia, the Netherlands, Slovenia, Spain, and Sweden). Interpretation Sex-neutral HPV vaccination is economically attractive in European tender-based settings. However, tendering mechanisms need to ensure that vaccination of boys will remain cost-effective at high vaccine uptake rates. Funding European Commission 7th Framework Programme and WHO.

Background Modelling studies have been widely used to inform human papillomavirus (HPV) vaccination policy decisions; however, many models exist and it is not known whether they produce consistent predictions of population-level effectiveness and herd effects. We did a systematic review and meta-analysis of model predictions of the long-term population-level effectiveness of vaccination against HPV 16, 18, 6, and 11 infection in women and men, to examine the variability in predicted herd effects, incremental benefit of vaccinating boys, and potential for HPV-vaccine-type elimination. Methods We searched MEDLINE and Embase for transmission-dynamic modelling studies published between Jan 1, 2009, and April 28, 2015, that predicted the population-level impact of vaccination on HPV 6, 11, 16, and 18 infections in high-income countries. We contacted authors to determine whether they were willing to produce new predictions for standardised scenarios. Strategies investigated were girls-only vaccination and girls and boys vaccination at age 12 years. Base-case vaccine characteristics were 100% efficacy and lifetime protection. We did sensitivity analyses by varying vaccination coverage, vaccine efficacy, and duration of protection. For all scenarios we pooled model predictions of relative reductions in HPV prevalence (RRprev) over time after vaccination and summarised results using the median and 10th and 90th percentiles (80% uncertainty intervals [UI]). Findings 16 of 19 eligible models from ten high-income countries provided predictions. Under base-case assumptions, 40% vaccination coverage and girls-only vaccination, the RRprev of HPV 16 among women and men was 0·53 (80% UI 0·46–0·68) and 0·36 (0·28–0·61), respectively, after 70 years. With 80% girls-only vaccination coverage, the RRprev of HPV 16 among women and men was 0·93 (0·90–1·00) and 0·83 (0·75–1·00), respectively. Vaccinating boys in addition to girls increased the RRprev of HPV 16 among women and men by 0·18 (0·13–0·32) and 0·35 (0·27–0·39) for 40% coverage, and 0·07 (0·00–0·10) and 0·16 (0·01–0·25) for 80% coverage, respectively. The RRprev were greater for HPV 6, 11, and 18 than for HPV 16 for all scenarios investigated. Finally at 80% coverage, most models predicted that girls and boys vaccination would eliminate HPV 6, 11, 16, and 18, with a median RRprev of 1·00 for women and men for all four HPV types. Variability in pooled findings was low, but increased with lower vaccination coverage and shorter vaccine protection (from lifetime to 20 years). Interpretation Although HPV models differ in structure, data used for calibration, and settings, our population-level predictions were generally concordant and suggest that strong herd effects are expected from vaccinating girls only, even with coverage as low as 20%. Elimination of HPV 16, 18, 6, and 11 is possible if 80% coverage in girls and boys is reached and if high vaccine efficacy is maintained over time. Funding Canadian Institutes of Health Research.

Summary The level of coverage and type-specific vaccine efficacy necessary to reduce or eliminate carcinogenic human papillomavirus (HPV) is chiefly determined by their propensity to persist. Therefore, HPV-16 infection and related cancers are the most difficult to eliminate through vaccination., Background Human papillomavirus (HPV) vaccination is still not reaching many high-risk populations. HPV16/18 vaccines offer cross-protection against other types, for example, HPV45. Both direct vaccine efficacy and indirect herd protection contribute to vaccination effectiveness. Methods We used a dynamic transmission model, calibrated to cervical screening data from Italy, to estimate vaccination effectiveness against HPV16 and HPV45 infection, assuming for HPV45 either 95% or lower cross-protection. Results Basic reproductive number was smaller (2.1 vs 4.0) and hence vaccine effectiveness and herd protection stronger for HPV45 than for HPV16. The largest difference in the reduction of infection prevalence in women

Summary: Chimera is a Bioconductor package that organizes, annotates, analyses and validates fusions reported by different fusion detection tools; current implementation can deal with output from bellerophontes, chimeraScan, deFuse, fusionCatcher, FusionFinder, FusionHunter, FusionMap, mapSplice, Rsubread, tophat-fusion and STAR. The core of Chimera is a fusion data structure that can store fusion events detected with any of the aforementioned tools. Fusions are then easily manipulated with standard R functions or through the set of functionalities specifically developed in Chimera with the aim of supporting the user in managing fusions and discriminating false-positive results. Availability and implementation: Chimera is implemented as a Bioconductor package in R. The package and the vignette can be downloaded at bioconductor.org. Contact: raffaele.calogero@unito.it Supplementary information: Supplementary data are available at Bioinformatics online.

Background. Gene fusions arising from chromosomal translocations have been implicated in cancer. RNA-seq has the potential to discover such rearrangements generating functional proteins (chimera/fusion). Recently, many methods for chimeras detection have been published. However, specificity and sensitivity of those tools were not extensively investigated in a comparative way.Results. We tested eight fusion-detection tools (FusionHunter, FusionMap, FusionFinder, MapSplice, deFuse, Bellerophontes, ChimeraScan, and TopHat-fusion) to detect fusion events using synthetic and real datasets encompassing chimeras. The comparison analysis run only on synthetic data could generate misleading results since we found no counterpart on real dataset. Furthermore, most tools report a very high number of false positive chimeras. In particular, the most sensitive tool, ChimeraScan, reports a large number of false positives that we were able to significantly reduce by devising and applying two filters to remove fusions not supported by fusion junction-spanning reads or encompassing large intronic regions.Conclusions. The discordant results obtained using synthetic and real datasets suggest that synthetic datasets encompassing fusion events may not fully catch the complexity of RNA-seq experiment. Moreover, fusion detection tools are still limited in sensitivity or specificity; thus, there is space for further improvement in the fusion-finder algorithms.

Background RNA-seq has the potential to discover genes created by chromosomal rearrangements. Fusion genes, also known as "chimeras", are formed by the breakage and re-joining of two different chromosomes. It is known that chimeras have been implicated in the development of cancer. Few publications in the past showed the presence of fusion events also in normal tissue, but with very limited overlaps between their results. More recently, two fusion genes in normal tissues were detected using both RNA-seq and protein data. Due to heterogeneous results in identifying chimeras in normal tissue, we decided to evaluate the efficacy of state of the art fusion finders in detecting chimeras in RNA-seq data from normal tissues. Results We compared the performance of six fusion-finder tools: FusionHunter, FusionMap, FusionFinder, MapSplice, deFuse and TopHat-fusion. To evaluate the sensitivity we used a synthetic dataset of fusion-products, called positive dataset; in these experiments FusionMap, FusionFinder, MapSplice, and TopHat-fusion are able to detect more than 78% of fusion genes. All tools were error prone with high variability among the tools, identifying some fusion genes not present in the synthetic dataset. To better investigate the false discovery chimera detection rate, synthetic datasets free of fusion-products, called negative datasets, were used. The negative datasets have different read lengths and quality scores, which allow detecting dependency of the tools on both these features. FusionMap, FusionFinder, mapSplice, deFuse and TopHat-fusion were error-prone. Only FusionHunter results were free of false positive. FusionMap gave the best compromise in terms of specificity in the negative dataset and of sensitivity in the positive dataset. Conclusions We have observed a dependency of the tools on read length, quality score and on the number of reads supporting each chimera. Thus, it is important to carefully select the software on the basis of the structure of the RNA-seq data under analysis. Furthermore, the sensitivity of chimera detection tools does not seem to be sufficient to provide results consistent with those obtained in normal tissues on the basis of fusion events extracted from published data.