Fried foods: a risk factor for laryngeal cancer?

The role of fried foods on laryngeal cancer risk was investigated in a case–control study from Italy and Switzerland on 527 cases and 1297 hospital controls. A significant increased risk was found for high consumption of fried meat, fish, eggs and potatoes, with odds ratios of 1.6, 3.1, 1.9 and 1.9, respectively

Spermatogonial stem cell sensitivity to capsaicin: An in vitro study

<p>Abstract</p> <p>Background</p> <p>Conflicting reports have been published on the sensitivity of spermatogenesis to capsaicin (CAP), the pungent ingredient of hot chili peppers. Here, the effect of CAP on germ cell survival was investigated by using two testis germ cell lines as a model. As CAP is a potent agonist of the transient receptor potential vanilloid receptor 1 (TRPV1) and no information was available of its expression in germ cells, we also studied the presence of TRPV1 in the cultured cells and in germ cells in situ.</p> <p>Methods</p> <p>The rat spermatogonial stem cell lines Gc-5spg and Gc-6spg were used to study the effects of different concentrations of CAP during 24 and 48 h. The response to CAP was first monitored by phase-contrast microscopy. As germ cells appear to undergo apoptosis in the presence of CAP, the activation of caspase 3 was studied using an anti activated caspase 3 antibody or by quantifying the amount of cells with DNA fragmentation using flow cytometry. Immunolocalization was done with an anti-TRPV1 antibody either with the use of confocal microscopy to follow live cell labeling (germ cells) or on Bouin fixed paraffin embedded testicular tissues. The expression of TRPV1 by the cell lines and germ cells was confirmed by Western blots.</p> <p>Results</p> <p>Initial morphological observations indicated that CAP at concentrations ranging from 150 uM to 250 uM and after 24 and 48 h of exposure, had deleterious apoptotic-like effects on both cell lines: A large population of the CAP treated cell cultures showed signs of DNA fragmentation and caspase 3 activation. Quantification of the effect demonstrated a significant effect of CAP with doses of 150 uM in the Gc-5spg cell line and 200 uM in the Gc-6spg cell line, after 24 h of exposure. The effect was dose and time dependent in both cell lines. TRPV1, the receptor for CAP, was found to be expressed by the spermatogonial stem cells in vitro and also by premeiotic germ cells in situ.</p> <p>Conclusion</p> <p>CAP adversely affects spermatogonial survival in vitro by inducing apoptosis to those cells and TRPV-1, a CAP receptor, may be involved in this effect as this receptor is expressed by mitotic germ cells.</p

Lung cancer risk among German male uranium miners: a cohort study, 1946–1998

From 1946 to 1990 extensive uranium mining was conducted in the southern parts of the former German Democratic Republic. The overall workforce included several 100 000 individuals. A cohort of 59 001 former male employees of the Wismut Company was established, forming a large retrospective uranium miners' cohort for the time period 1946–1998. Mean duration of follow-up was 30.5 years with a total of 1 801 630 person-years. Loss to follow-up was low at 5.3%. Of the workers, 16 598 (28.1%) died during the study period. Based on 2388 lung cancer deaths, the radon-related lung cancer risk is evaluated. The excess relative risk (ERR) per working level month (WLM) was estimated as 0.21% (95% CI: 0.18–0.24). It was dependent on time since exposure and on attained age. The highest ERR/WLM was observed 15–24 years after exposure and in the youngest age group (<55 years of age). While a strong inverse exposure-rate effect was detected for high exposures, no significant association was detected at exposures below 100 WLM. Excess relative risk /WLM was not modified by duration of exposure. The results would indicate the need to re-estimate the effects of risk modifying factors in current risk models as duration of exposure did not modify the ERR/WLM and there was only a modest decline of ERR/WLM with increasing time since exposure

Quantification of ETS exposure in hospitality workers who have never smoked

<p>Abstract</p> <p>Background</p> <p>Environmental Tobacco Smoke (ETS) was classified as human carcinogen (K1) by the German Research Council in 1998. According to epidemiological studies, the relative risk especially for lung cancer might be twice as high in persons who have never smoked but who are in the highest exposure category, for example hospitality workers. In order to implement these results in the German regulations on occupational illnesses, a valid method is needed to retrospectively assess the cumulative ETS exposure in the hospitality environment.</p> <p>Methods</p> <p>A literature-based review was carried out to locate a method that can be used for the German hospitality sector. Studies assessing ETS exposure using biological markers (for example urinary cotinine, DNA adducts) or questionnaires were excluded. Biological markers are not considered relevant as they assess exposure only over the last hours, weeks or months. Self-reported exposure based on questionnaires also does not seem adequate for medico-legal purposes. Therefore, retrospective exposure assessment should be based on mathematical models to approximate past exposure.</p> <p>Results</p> <p>For this purpose a validated model developed by Repace and Lowrey was considered appropriate. It offers the possibility of retrospectively assessing exposure with existing parameters (such as environmental dimensions, average number of smokers, ventilation characteristics and duration of exposure). The relative risk of lung cancer can then be estimated based on the individual cumulative exposure of the worker.</p> <p>Conclusion</p> <p>In conclusion, having adapted it to the German hospitality sector, an existing mathematical model appears to be capable of approximating the cumulative exposure. However, the level of uncertainty of these approximations has to be taken into account, especially for diseases with a long latency period such as lung cancer.</p

APOBEC signature mutation generates an oncogenic enhancer that drives LMO1 expression in T-ALL

Oncogenic driver mutations are those that provide a proliferative or survival advantage to neoplastic cells, resulting in clonal selection. Although most cancer-causing mutations have been detected in the protein-coding regions of the cancer genome; driver mutations have recently also been discovered within noncoding genomic sequences. Thus, a current challenge is to gain precise understanding of how these unique genomic elements function in cancer pathogenesis, while clarifying mechanisms of gene regulation and identifying new targets for therapeutic intervention. Here we report a C-to-T single nucleotide transition that occurs as a somatic mutation in noncoding sequences 4 kb upstream of the transcriptional start site of the LMO1 oncogene in primary samples from patients with T-cell acute lymphoblastic leukaemia. This single nucleotide alteration conforms to an APOBEC-like cytidine deaminase mutational signature, and generates a new binding site for the MYB transcription factor, leading to the formation of an aberrant transcriptional enhancer complex that drives high levels of expression of the LMO1 oncogene. Since APOBEC-signature mutations are common in a broad spectrum of human cancers, we suggest that noncoding nucleotide transitions such as the one described here may activate potent oncogenic enhancers not only in T-lymphoid cells but in other cell lineages as well

A computational framework for complex disease stratification from multiple large-scale datasets.

BACKGROUND: Multilevel data integration is becoming a major area of research in systems biology. Within this area, multi-'omics datasets on complex diseases are becoming more readily available and there is a need to set standards and good practices for integrated analysis of biological, clinical and environmental data. We present a framework to plan and generate single and multi-'omics signatures of disease states. METHODS: The framework is divided into four major steps: dataset subsetting, feature filtering, 'omics-based clustering and biomarker identification. RESULTS: We illustrate the usefulness of this framework by identifying potential patient clusters based on integrated multi-'omics signatures in a publicly available ovarian cystadenocarcinoma dataset. The analysis generated a higher number of stable and clinically relevant clusters than previously reported, and enabled the generation of predictive models of patient outcomes. CONCLUSIONS: This framework will help health researchers plan and perform multi-'omics big data analyses to generate hypotheses and make sense of their rich, diverse and ever growing datasets, to enable implementation of translational P4 medicine