Occurrence of False Positive Results for the Detection of Carbapenemases in Carbapenemase-Negative Escherichia coli and Klebsiella pneumoniae Isolates

Adequate detection of the production of carbapenemase in Enterobacteriaceae isolates is crucial for infection control measures and the appropriate choice of antimicrobial therapy. In this study, we investigated the frequency of false positive results for the detection of carbapenemases in carbapenemase-negative Escherichia coli and Klebsiella pneumoniae clinical isolates by the modified Hodge test (MHT). Three hundred and one E. coli and K. pneumoniae clinical isolates were investigated. All produced extended spectrum β-lactamases (ESBLs) but were susceptible to carbapenems. Antimicrobial susceptibility testing was performed by the disk diffusion and agar dilution methods. The MHT was performed using the standard inoculum of test organisms recommended by the CLSI. Genes that encoded ESBLs and carbapenemases were identified by PCR and DNA sequencing. Among the 301 clinical isolates, none of the isolates conformed to the criteria for carbapenemase screening recommended by the CLSI. The susceptibility rates for imipenem, meropenem, and ertapenem all were 100.0%, 100.0%, and 100.0%, respectively. Of the 301 E. coli and K. pneumoniae isolates, none produced carbapenemase. The MHT gave a positive result for 3.3% (10/301) of the isolates. False positive results can occur when the MHT is used to detect carbapenemase in ESBL-producing isolates and clinical laboratories must be aware of this fact

Serum estradiol levels associated with specific gene expression patterns in normal breast tissue and in breast carcinomas

Abstract Background High serum levels of estradiol are associated with increased risk of postmenopausal breast cancer. Little is known about the gene expression in normal breast tissue in relation to levels of circulating serum estradiol. Methods We compared whole genome expression data of breast tissue samples with serum hormone levels using data from 79 healthy women and 64 breast cancer patients. Significance analysis of microarrays (SAM) was used to identify differentially expressed genes and multivariate linear regression was used to identify independent associations. Results Six genes (SCGB3A1, RSPO1, TLN2, SLITRK4, DCLK1, PTGS1) were found differentially expressed according to serum estradiol levels (FDR = 0). Three of these independently predicted estradiol levels in a multivariate model, as SCGB3A1 (HIN1) and TLN2 were up-regulated and PTGS1 (COX1) was down-regulated in breast samples from women with high serum estradiol. Serum estradiol, but none of the differentially expressed genes were significantly associated with mammographic density, another strong breast cancer risk factor. In breast carcinomas, expression of GREB1 and AREG was associated with serum estradiol in all cancers and in the subgroup of estrogen receptor positive cases. Conclusions We have identified genes associated with serum estradiol levels in normal breast tissue and in breast carcinomas. SCGB3A1 is a suggested tumor suppressor gene that inhibits cell growth and invasion and is methylated and down-regulated in many epithelial cancers. Our findings indicate this gene as an important inhibitor of breast cell proliferation in healthy women with high estradiol levels. In the breast, this gene is expressed in luminal cells only and is methylated in non-BRCA-related breast cancers. The possibility of a carcinogenic contribution of silencing of this gene for luminal, but not basal-like cancers should be further explored. PTGS1 induces prostaglandin E2 (PGE2) production which in turn stimulates aromatase expression and hence increases the local production of estradiol. This is the first report studying such associations in normal breast tissue in humans

Adjusting for BMI in analyses of volumetric mammographic density and breast cancer risk

Abstract Background Fully automated assessment of mammographic density (MD), a biomarker of breast cancer risk, is being increasingly performed in screening settings. However, data on body mass index (BMI), a confounder of the MD–risk association, are not routinely collected at screening. We investigated whether the amount of fat in the breast, as captured by the amount of mammographic non-dense tissue seen on the mammographic image, can be used as a proxy for BMI when data on the latter are unavailable. Methods Data from a UK case control study (numbers of cases/controls: 414/685) and a Norwegian cohort study (numbers of cases/non-cases: 657/61059), both with volumetric MD measurements (dense volume (DV), non-dense volume (NDV) and percent density (%MD)) from screening-age women, were analysed. BMI (self-reported) and NDV were taken as measures of adiposity. Correlations between BMI and NDV, %MD and DV were examined after log-transformation and adjustment for age, menopausal status and parity. Logistic regression models were fitted to the UK study, and Cox regression models to the Norwegian study, to assess associations between MD and breast cancer risk, expressed as odds/hazard ratios per adjusted standard deviation (OPERA). Adjustments were first made for standard risk factors except BMI (minimally adjusted models) and then also for BMI or NDV. OPERA pooled relative risks (RRs) were estimated by fixed-effect models, and between-study heterogeneity was assessed by the I 2 statistics. Results BMI was positively correlated with NDV (adjusted r = 0.74 in the UK study and r = 0.72 in the Norwegian study) and with DV (r = 0.33 and r = 0.25, respectively). Both %MD and DV were positively associated with breast cancer risk in minimally adjusted models (pooled OPERA RR (95% confidence interval): 1.34 (1.25, 1.43) and 1.46 (1.36, 1.56), respectively; I 2 = 0%, P >0.48 for both). Further adjustment for BMI or NDV strengthened the %MD–risk association (1.51 (1.41, 1.61); I 2 = 0%, P = 0.33 and 1.51 (1.41, 1.61); I 2 = 0%, P = 0.32, respectively). Adjusting for BMI or NDV marginally affected the magnitude of the DV–risk association (1.44 (1.34, 1.54); I 2 = 0%, P = 0.87 and 1.49 (1.40, 1.60); I 2 = 0%, P = 0.36, respectively). Conclusions When volumetric MD–breast cancer risk associations are investigated, NDV can be used as a measure of adiposity when BMI data are unavailable

Adaptation of Brucella melitensis Antimicrobial Susceptibility Testing to the ISO 20776 Standard and Validation of the Method

This article belongs to the Special Issue Emerging Themes in Brucella and Brucellosis.Brucellosis, mainly caused by Brucella (B.) melitensis, is associated with a risk of chronification and relapses. Antimicrobial susceptibility testing (AST) standards for B. melitensis are not available, and the agent is not yet listed in the EUCAST breakpoint tables. CLSI recommendations for B. melitensis exist, but they do not fulfill the requirements of the ISO 20776 standard regarding the culture medium and the incubation conditions. Under the third EU Health Programme, laboratories specializing in the diagnostics of highly pathogenic bacteria in their respective countries formed a working group within a Joint Action aiming to develop a suitable method for the AST of B. melitensis. Under the supervision of EUCAST representatives, this working group adapted the CLSI M45 document to the ISO 20776 standard after testing and validation. These adaptations included the comparison of various culture media, culture conditions and AST methods. A Standard Operation Procedure was derived and an interlaboratory validation was performed in order to evaluate the method. The results showed pros and cons for both of the two methods but also indicate that it is not necessary to abandon Mueller–Hinton without additives for the AST of B. melitensis.This research was funded by the EU Health Programme 2014–2020, through the Consumers, Health, Agriculture and Food Executive Agency (CHAFEA, European Commission), the Joint Action EMERGE (CHAFEA n° 677 066) and the Joint Action SHARP (848096-SHARP JA).info:eu-repo/semantics/publishedVersio

Recent breast cancer incidence trends according to hormone therapy use: the California Teachers Study cohort

Abstract Introduction Recent, international declines in breast cancer incidence are unprecedented, and the causes remain controversial. Few data sources can address breast cancer incidence trends according to pertinent characteristics like hormone therapy use history. Methods We used the prospective California Teachers Study to evaluate changes in self-reported use of menopausal hormone therapy (HT) between 1995 to 1996 and 2005 to 2006 and age-adjusted breast cancer incidence among 74,647 participants aged 50 years or older. Breast cancer occurrence was determined by linkage with the California Cancer Registry. Results During 517,286 woman years of follow up, 565 in situ and 2,668 invasive breast cancers were diagnosed. In situ breast cancer incidence rates in this population did not change significantly from 2000 to 2002 to 2003 to 2005, whereas rates of invasive breast cancer declined significantly by 26.0% from 528.0 (95% confidence intervals (CI) = 491.1, 564.9) per 100,000 women in 2000 to 2002 to 390.6 (95% CI = 355.6, 425.7) in 2003 to 2005. The decline in invasive breast cancer incidence rates was restricted to estrogen receptor-positive tumors. In 1996 to 1999 and 2000 to 2002 invasive breast cancer incidence was higher for women who reported current HT use especially estrogen-progestin (EP) use at baseline than for never or past users; but by 2003 to 2005 rates were comparable between these groups. For women who were taking EP in 2001 to 2002,75% of whom had stopped use by 2005 to 2006, incidence had declined 30.6% by 2003 to 2005 (P = 0.001); whereas incidence did not change significantly for those who never took HT (P = 0.33). Conclusions Few data resources can examine prospectively individual HT use and breast cancer diagnosis. Stable in situ breast cancer rates imply consistent levels of screening and suggest recent declines in invasive breast cancer to be explained predominantly by changes in HT use

Measurement challenge : protocol for international case–control comparison of mammographic measures that predict breast cancer risk

Introduction: For women of the same age and body mass index, increased mammographic density is one of the strongest predictors of breast cancer risk. There are multiple methods of measuring mammographic density and other features in a mammogram that could potentially be used in a screening setting to identify and target women at high risk of developing breast cancer. However, it is unclear which measurement method provides the strongest predictor of breast cancer risk. Methods and analysis: The measurement challenge has been established as an international resource to offer a common set of anonymised mammogram images for measurement and analysis. To date, full field digital mammogram images and core data from 1650 cases and 1929 controls from five countries have been collated. The measurement challenge is an ongoing collaboration and we are continuing to expand the resource to include additional image sets across different populations (from contributors) and to compare additional measurement methods (by challengers). The intended use of the measurement challenge resource is for refinement and validation of new and existing mammographic measurement methods. The measurement challenge resource provides a standardised dataset of mammographic images and core data that enables investigators to directly compare methods of measuring mammographic density or other mammographic features in case/control sets of both raw and processed images, for the purposes of the comparing their predictions of breast cancer risk. Ethics and dissemination: Challengers and contributors are required to enter a Research Collaboration Agreement with the University of Melbourne prior to participation in the measurement challenge. The Challenge database of collated data and images are stored in a secure data repository at the University of Melbourne. Ethics approval for the measurement challenge is held at University of Melbourne (HREC ID 0931343.3)

Hormone-related risk factors for breast cancer in women under age 50 years by estrogen and progesterone receptor status: results from a case–control and a case–case comparison

INTRODUCTION: It has been suggested that hormonal risk factors act predominantly on estrogen receptor and progesterone receptor (ER/PR)-positive breast cancers. However, the data have been inconsistent, especially in younger women. METHODS: We evaluated the impact of age at menarche, pregnancy history, duration of breastfeeding, body mass index, combined oral contraceptive use, and alcohol consumption on breast cancer risk by ER/PR status in 1,725 population-based case patients and 440 control subjects aged 20 to 49 years identified within neighborhoods of case patients. We used multivariable unconditional logistic regression methods to conduct case–control comparisons overall as well as by ER/PR status of the cases, and to compare ER(+)PR(+ )with ER(-)PR(- )case patients. RESULTS: The number of full-term pregnancies was inversely associated with the risk of ER(+)PR(+ )breast cancer (p(trend )= 0.005), whereas recent average alcohol consumption was associated with an increased risk of ER(+)PR(+ )breast cancer (p(trend )= 0.03). Neither of these two factors was associated with the risk of ER(- )PR(- )breast cancer. Late age at menarche and a longer duration of breastfeeding were both associated with decreased breast cancer risk, irrespective of receptor status (all p(trend)≤ 0.03). CONCLUSION: Our results suggest that the number of full-term pregnancies and recent alcohol consumption affect breast cancer risk in younger women predominantly through estrogen and progesterone mediated by their respective receptors. Late age at menarche and breastfeeding may act through different hormonal mechanisms

Expression levels of uridine 5'-diphospho-glucuronosyltransferase genes in breast tissue from healthy women are associated with mammographic density

Introduction Mammographic density (MD), as assessed from film screen mammograms, is determined by the relative content of adipose, connective and epithelial tissue in the female breast. In epidemiological studies, a high percentage of MD confers a four to six fold risk elevation of developing breast cancer, even after adjustment for other known breast cancer risk factors. However, the biologic correlates of density are little known. Methods Gene expression analysis using whole genome arrays was performed on breast biopsies from 143 women; 79 women with no malignancy (healthy women) and 64 newly diagnosed breast cancer patients, both included from mammographic centres. Percent MD was determined using a previously validated, computerized method on scanned mammograms. Significance analysis of microarrays (SAM) was performed to identify genes influencing MD and a linear regression model was used to assess the independent contribution from different variables to MD. Results SAM-analysis identified 24 genes differentially expressed between samples from breasts with high and low MD. These genes included three uridine 5'-diphospho-glucuronosyltransferase (UGT) genes and the oestrogen receptor gene (ESR1). These genes were down-regulated in samples with high MD compared to those with low MD. The UGT gene products, which are known to inactivate oestrogen metabolites, were also down-regulated in tumour samples compared to samples from healthy individuals. Several single nucleotide polymorphisms (SNPs) in the UGT genes associated with the expression of UGT and other genes in their vicinity were identified. Conclusions Three UGT enzymes were lower expressed both in breast tissue biopsies from healthy women with high MD and in biopsies from newly diagnosed breast cancers. The association was strongest amongst young women and women using hormonal therapy. UGT2B10 predicts MD independently of age, hormone therapy and parity. Our results indicate that down-regulation of UGT genes in women exposed to female sex hormones is associated with high MD and might increase the risk of breast cancer

Gene expression profiles of breast biopsies from healthy women identify a group with claudin-low features

Background Increased understanding of the variability in normal breast biology will enable us to identify mechanisms of breast cancer initiation and the origin of different subtypes, and to better predict breast cancer risk. Methods Gene expression patterns in breast biopsies from 79 healthy women referred to breast diagnostic centers in Norway were explored by unsupervised hierarchical clustering and supervised analyses, such as gene set enrichment analysis and gene ontology analysis and comparison with previously published genelists and independent datasets. Results Unsupervised hierarchical clustering identified two separate clusters of normal breast tissue based on gene-expression profiling, regardless of clustering algorithm and gene filtering used. Comparison of the expression profile of the two clusters with several published gene lists describing breast cells revealed that the samples in cluster 1 share characteristics with stromal cells and stem cells, and to a certain degree with mesenchymal cells and myoepithelial cells. The samples in cluster 1 also share many features with the newly identified claudin-low breast cancer intrinsic subtype, which also shows characteristics of stromal and stem cells. More women belonging to cluster 1 have a family history of breast cancer and there is a slight overrepresentation of nulliparous women in cluster 1. Similar findings were seen in a separate dataset consisting of histologically normal tissue from both breasts harboring breast cancer and from mammoplasty reductions. Conclusion This is the first study to explore the variability of gene expression patterns in whole biopsies from normal breasts and identified distinct subtypes of normal breast tissue. Further studies are needed to determine the specific cell contribution to the variation in the biology of normal breasts, how the clusters identified relate to breast cancer risk and their possible link to the origin of the different molecular subtypes of breast cancer