Weibull regression with Bayesian variable selection to identify prognostic tumour markers of breast cancer survival.

As data-rich medical datasets are becoming routinely collected, there is a growing demand for regression methodology that facilitates variable selection over a large number of predictors. Bayesian variable selection algorithms offer an attractive solution, whereby a sparsity inducing prior allows inclusion of sets of predictors simultaneously, leading to adjusted effect estimates and inference of which covariates are most important. We present a new implementation of Bayesian variable selection, based on a Reversible Jump MCMC algorithm, for survival analysis under the Weibull regression model. A realistic simulation study is presented comparing against an alternative LASSO-based variable selection strategy in datasets of up to 20,000 covariates. Across half the scenarios, our new method achieved identical sensitivity and specificity to the LASSO strategy, and a marginal improvement otherwise. Runtimes were comparable for both approaches, taking approximately a day for 20,000 covariates. Subsequently, we present a real data application in which 119 protein-based markers are explored for association with breast cancer survival in a case cohort of 2287 patients with oestrogen receptor-positive disease. Evidence was found for three independent prognostic tumour markers of survival, one of which is novel. Our new approach demonstrated the best specificity.PJN and SR were funded by the Medical Research Council. PJN also acknowledges partial support from the NIHR Cambridge Biomedical Research Centre.This is the accepted manuscript. The final version is available from SAGE at http://dx.doi.org/10.1177/096228021454874

Seatbelt use and risk of major injuries sustained by vehicle occupants during motor-vehicle crashes: A systematic review and meta-analysis of cohort studies

BackgroundIn 2004, a World Health Report on road safety called for enforcement of measures such as seatbelt use, effective at minimizing morbidity and mortality caused by road traffic accidents. However, injuries caused by seatbelt use have also been described. Over a decade after publication of the World Health Report on road safety, this study sought to investigate the relationship between seatbelt use and major injuries in belted compared to unbelted passengers.MethodsCohort studies published in English language from 2005 to 2018 were retrieved from seven databases. Critical appraisal of studies was carried out using the Scottish Intercollegiate Guidelines Network (SIGN) checklist. Pooled risk of major injuries was assessed using the random effects meta-analytic model. Heterogeneity was quantified using I-squared and Tau-squared statistics. Funnel plots and Egger's test were used to investigate publication bias. This review is registered in PROSPERO (CRD42015020309).ResultsEleven studies, all carried out in developed countries were included. Overall, the risk of any major injury was significantly lower in belted passengers compared to unbelted passengers (RR 0.47; 95%CI, 0.29 to 0.80; I-2=99.7; P=0.000). When analysed by crash types, belt use significantly reduced the risk of any injury (RR 0.35; 95%CI, 0.24 to 0.52). Seatbelt use reduces the risk of facial injuries (RR=0.56, 95% CI=0.37 to 0.84), abdominal injuries (RR=0.87; 95% CI=0.78 to 0.98) and, spinal injuries (RR=0.56, 95% CI=0.37 to 0.84). However, we found no statistically significant difference in risk of head injuries (RR=0.49; 95% CI=0.22 to 1.08), neck injuries (RR=0.69: 95%CI 0.07 to 6.44), thoracic injuries (RR 0.96, 95%CI, 0.74 to 1.24), upper limb injuries (RR=1.05, 95%CI 0.83 to 1.34) and lower limb injuries (RR=0.77, 95%CI 0.58 to 1.04) between belted and non-belted passengers.ConclusionIn sum, the risk of most major road traffic injuries is lower in seatbelt users. Findings were inconclusive regarding seatbelt use and susceptibility to thoracic, head and neck injuries during road traffic accidents. Awareness should be raised about the dangers of inadequate seatbelt use. Future research should aim to assess the effects of seatbelt use on major injuries by crash type

The malignant phenotype in breast cancer is driven by eIF4A1-mediated changes in the translational landscape

Human mRNA DeXD/H-box helicases are ubiquitous molecular motors that are required for the majority of cellular processes that involve RNA metabolism. One of the most abundant is eIF4A, which is required during the initiation phase of protein synthesis to unwind regions of highly structured mRNA that would otherwise impede the scanning ribosome. Dysregulation of protein synthesis is associated with tumorigenesis, but little is known about the detailed relationships between RNA helicase function and the malignant phenotype in solid malignancies. Therefore, immunohistochemical analysis was performed on over 3000 breast tumors to investigate the relationship among expression of eIF4A1, the helicase-modulating proteins eIF4B, eIF4E and PDCD4, and clinical outcome. We found eIF4A1, eIF4B and eIF4E to be independent predictors of poor outcome in ER-negative disease, while in contrast, the eIF4A1 inhibitor PDCD4 was related to improved outcome in ER-positive breast cancer. Consistent with these data, modulation of eIF4A1, eIF4B and PCDC4 expression in cultured MCF7 cells all restricted breast cancer cell growth and cycling. The eIF4A1-dependent translatome of MCF7 cells was defined by polysome profiling, and was shown to be highly enriched for several classes of oncogenic genes, including G-protein constituents, cyclins and protein kinases, and for mRNAs with G/C-rich 5′UTRs with potential to form G-quadruplexes and with 3′UTRs containing microRNA target sites. Overall, our data show that dysregulation of mRNA unwinding contributes to the malignant phenotype in breast cancer via preferential translation of a class of genes involved in pro-oncogenic signaling at numerous levels. Furthermore, immunohistochemical tests are promising biomarkers for tumors sensitive to anti-helicase therapies

Variation in the Male Pheromones and Mating Success of Wild Caught Drosophila melanogaster

Drosophila melanogaster males express two primary cuticular hydrocarbons (male-predominant hydrocarbons). These act as sex pheromones by influencing female receptivity to mating. The relative quantities of these hydrocarbons vary widely among natural populations and can contribute to variation in mating success. We tested four isofemale lines collected from a wild population to assess the effect of intrapopulation variation in male-predominant hydrocarbons on mating success. The receptivity of laboratory females to males of the four wild-caught lines varied significantly, but not consistently in the direction predicted by variation in male-predominant hydrocarbons. Receptivity of the wild-caught females to laboratory males also varied significantly, but females from lines with male-predominant hydrocarbon profiles closer to a more cosmopolitan one did not show a correspondingly strong mating bias toward a cosmopolitan male. Among wild-caught lines, the male-specific ejaculatory bulb lipid, cis-vaccenyl acetate, varied more than two-fold, but was not associated with variation in male mating success. We observed a strong inverse relationship between the receptivity of wild-caught females and the mating success of males from their own lines, when tested with laboratory flies of the opposite sex

Immunohistochemistry profiles of breast ductal carcinoma: factor analysis of digital image analysis data

<p>Abstract</p> <p>Background</p> <p>Molecular studies of breast cancer revealed biological heterogeneity of the disease and opened new perspectives for personalized therapy. While multiple gene expression-based systems have been developed, current clinical practice is largely based upon conventional clinical and pathologic criteria. This gap may be filled by development of combined multi-IHC indices to characterize biological and clinical behaviour of the tumours. Digital image analysis (DA) with multivariate statistics of the data opens new opportunities in this field.</p> <p>Methods</p> <p>Tissue microarrays of 109 patients with breast ductal carcinoma were stained for a set of 10 IHC markers (ER, PR, HER2, Ki67, AR, BCL2, HIF-1α, SATB1, p53, and p16). Aperio imaging platform with the Genie, Nuclear and Membrane algorithms were used for the DA. Factor analysis of the DA data was performed in the whole group and hormone receptor (HR) positive subgroup of the patients (n = 85).</p> <p>Results</p> <p>Major factor potentially reflecting aggressive disease behaviour (i-Grade) was extracted, characterized by opposite loadings of ER/PR/AR/BCL2 and Ki67/HIF-1α. The i-Grade factor scores revealed bimodal distribution and were strongly associated with higher Nottingham histological grade (G) and more aggressive intrinsic subtypes. In HR-positive tumours, the aggressiveness of the tumour was best defined by positive Ki67 and negative ER loadings. High Ki67/ER factor scores were strongly associated with the higher G and Luminal B types, but also were detected in a set of G1 and Luminal A cases, potentially indicating high risk patients in these categories. Inverse relation between HER2 and PR expression was found in the HR-positive tumours pointing at differential information conveyed by the ER and PR expression. SATB1 along with HIF-1α reflected the second major factor of variation in our patients; in the HR-positive group they were inversely associated with the HR and BCL2 expression and represented the major factor of variation. Finally, we confirmed high expression levels of p16 in Triple-negative tumours.</p> <p>Conclusion</p> <p>Factor analysis of multiple IHC biomarkers measured by automated DA is an efficient exploratory tool clarifying complex interdependencies in the breast ductal carcinoma IHC profiles and informative value of single IHC markers. Integrated IHC indices may provide additional risk stratifications for the currently used grading systems and prove to be useful in clinical outcome studies.</p> <p>Virtual Slides</p> <p>The virtual slide(s) for this article can be found here: <url>http://www.diagnosticpathology.diagnomx.eu/vs/1512077125668949</url></p

Biomarkers characterization of circulating tumour cells in breast cancer patients

Introduction: Increasing evidence supports the view that the detection of circulating tumor cells (CTCs) predicts outcomes of nonmetastatic breast cancer patients. CTCs differ genetically from the primary tumor and may contribute to variations in prognosis and response to therapy. As we start to understand more about the biology of CTCs, we can begin to address how best to treat this form of disease. Methods: Ninety-eight nonmetastatic breast cancer patients were included in this study. CTCs were isolated by immunomagnetic techniques using magnetic beads labelled with a multi-CK-specific antibody (CK3-11D5) and CTC detection through immunocytochemical methods. Estrogen receptor, progesterone receptor and epidermal growth factor receptor (EGFR) were evaluated by immunofluorescence experiments and HER2 and TOP2A by fluorescence in situ hybridization. We aimed to characterize this set of biomarkers in CTCs and correlate it with clinical-pathological characteristics. Results: Baseline detection rate was 46.9% ≥ 1 CTC/30 ml threshold. CTC-positive cells were more frequent in HER2-negative tumors (p = 0.046). In patients younger than 50 years old, HER2-amplified and G1-G2 tumors had a higher possibility of being nondetectable CTCs. Heterogeneous expression of hormonal receptors (HRs) in samples from the same patients was found. Discordances between HR expression, HER2 and TOP2A status in CTCs and their primary tumor were found in the sequential blood samples. Less that 35% of patients switched their CTC status after receiving chemotherapy. EGFR-positive CTCs were associated with Luminal tumors (p = 0.03). Conclusions: This is the largest exploratory CTC biomarker analysis in nonmetastatic BC patients. Our study suggests that CTC biomarkers profiles might be useful as a surrogate marker for therapeutic selection and monitoring since heterogeneity of the biomarker distribution in CTCs and the lack of correlation with the primary tumor biomarker status were found. Further exploration of the association between EGFR-positive CTCs and Luminal tumors is warranted