The objective was to evaluate the hypothesis that growth-differentiation factor 15 (GDF-15) is an independent marker of the long-term risk for both cardiovascular disease and cancer morbidity beyond clinical and biochemical risk factors. Plasma obtained at age 71 was available from 940 subjects in the Uppsala Longitudinal Study of Adult Men (ULSAM) cohort. Complete mortality and morbidity data were obtained from public registries. At baseline there were independent associations between GDF-15 and current smoking, diabetes mellitus, biomarkers of cardiac (high-sensitivity troponin-T, NT-proBNP) and renal dysfunction (cystatin-C) and inflammatory activity (C-reactive protein), and previous cardiovascular disease (CVD). During 10 years follow-up there occurred 265 and 131 deaths, 115 and 46 cardiovascular deaths, and 185 and 86 events with coronary heart disease mortality or morbidity in the respective total cohort (n=940) and non-CVD (n=561) cohort. After adjustment for conventional cardiovascular risk factors, one SD increase in log GDF-15 were, in the respective total and non-CVD populations, associated with 48% (95%CI 26 to 73%, p<0.001) and 67% (95%CI 28 to 217%, p<0.001) incremental risk of cardiovascular mortality, 48% (95%CI 33 to 67%, p<0.001) and 61% (95%CI 38 to 89%, p<0.001) of total mortality and 36% (95%CI 19 to 56%, p<0.001) and 44% (95%CI 17 to 76%, p<0.001) of coronary heart disease morbidity and mortality. The corresponding incremental increase for cancer mortality in the respective total and non-cancer disease (n=882) population was 46% (95%CI 21 to 77%, p<0.001) and 38% (95%CI 12 to 70%, p<0.001) and for cancer morbidity and mortality in patients without previous cancer disease 30% (95%CI 12 to 51%, p<0.001). In conclusion, in elderly men, GDF-15 improves prognostication of both cardiovascular, cancer mortality and morbidity beyond established risk factors and biomarkers of cardiac, renal dysfunction and inflammation.
Breast cancer is one of the most prevalent cancers in women, with more than 240,000 new cases reported in the United States in 2011. Classification of breast cancer based upon hormone and growth factor receptor profiling shows that approximately 70% of all breast cancers express estrogen receptor-α. Thus, drugs that either block estrogen biosynthesis (aromatase inhibitors like Letrozole), or compete with estrogen for estrogen receptor (ER) binding (selective ER modulators including tamoxifen; TAM) and/or cause ER degradation (selective estrogen receptor downregulators such as fulvestrant), are among the most prescribed targeted therapeutics for breast cancer. However, overall clinical benefit from the use of these drugs is often limited by resistance; ER+ breast cancers either fail to respond to endocrine therapies initially (de novo resistance), or they respond and then lose sensitivity over time (acquired resistance). While several preclinical studies postulate how antiestrogen resistance occurs, for the most part, the molecular mechanism(s) of resistance is unknown.
breast cancer; antiestrogen resistance; glucose-regulated protein 78; unfolded protein response; autophagy; AMP-activated protein kinase; MTOR
Understanding the molecular changes that drive an acquired antiestrogen resistance phenotype is of major clinical relevance. Previous methodologies for addressing this question have taken a single gene/pathway approach and the resulting gains have been limited in terms of their clinical impact. Recent systems biology approaches allow for the integration of data from high throughput “-omics” technologies. We highlight recent advances in the field of antiestrogen resistance with a focus on transcriptomics, proteomics and methylomics.
Systems biology; breast cancer; estrogens; antiestrogens
Some countries fortify flour with folic acid to prevent neural tube defects but others do not, partly because of concerns about cancer risks. We aimed to assess the effects of folic acid supplementation on site-specific cancer rates in the randomised trials.
Meta-analyses of data on each individual in all placebo-controlled trials of folic acid for prevention of cardiovascular disease (10 trials, n=46,969) or colorectal adenoma (3 trials, n=2652) that recorded cancer incidence and recruited >500 participants. All trials were evenly randomised. Risk ratios (RRs) compare those allocated folic acid vs those allocated placebo, giving cancer incidence rate ratios (among those still free of cancer) during, but not after the scheduled treatment period.
During a weighted mean follow-up duration of 5.5 years, allocation to folic acid quadrupled plasma folate, but had no statistically significant effect on overall cancer incidence (1904 vs 1809 cancers, RR=1.06 [95%CI 0.99–1.13], p=0.10; trend with duration of treatment p=0.46). There was no significant heterogeneity between the results of individual trials (p=0.23), or between the cadiovascular prevention trials and the adenoma prevention trials (p=0.13). Moreover, there was no significant effect of folic acid supplementation on the incidence of cancer of the large intestine, prostate, lung, breast or any other specific site.
Folic acid supplementation does not substantially increase or decrease site-specific cancer incidence during the first 5 years of treatment.
British Heart Foundation, Medical Research Council, Cancer Research UK, Food Standards Agency.
E-selectin (SELE) mediates the rolling and adhesion of leukocytes on activated endothelial cells and plays a critial role in the pathogenesis of coronary artery disease (CAD). Associatons between the A561C and G98T polymorphisms of the SELE gene and CAD risk were investigated broadly, but the results were inconsistent. In the present study, we performed a meta-analysis to systematically evaluate the associations between the two polymorphisms and the risk of CAD.
Comprehensive research was conducted to identify relevant studies. The fixed or random effect model was selected based on the heterogeneity among studies, which was evaluated with Q-test and Ι2. Meta-regression was used to explore the potential sources of between-study heterogeneity. Peters's linear regression test was used to estimate the publication bias.
Overall, 24 articles involving 3694 cases and 3469 controls were included. After excluding articles deviating from Hardy–Weinberg equilibrium in controls and sensitive analysis, our meta-analysis showed a significant association between the A561C ploymprphism and CAD in dominant (OR = 1.84, 95% CI = 1.56–2.16) and codominant (OR = 1.74, 95% CI = 1.49–2.03) models. As for the G98T polymorphism, significantly increased CAD risk was observed in dominant (OR = 1.47, 95% CI = 1.16–1.87) and codominant (OR = 1.48, 95% CI = 1.18–1.86) models, but after subgroup analysis, the association was not significant among Caucasians in dominant (OR = 1.58, 95% CI = 0.73–3.41) and codominant (OR = 1.58, 95% CI = 0.79–3.20) models.
Despite some limitations, our meta-analysis suggested that the SELE gene polymorphisms (A561C, G98T) were significantly associated with increased risk of CAD. However, after subgroup analysis no significant association was found among Caucasians for the G98T polymorphism, which may be due to the small sample size and other confounding factors. Future investigations with multicenter, large-scale, and multi-ethnic groups are needed.
The prognostic importance of B-type natriuretic peptide (BNP) or N-terminal pro BNP (NT-proBNP) in patients with end-stage renal disease (ESRD) remains controversial.
We conducted an unrestricted search from the MEDLINE and EMBASE in all languages that were published between 1966 and Augest2013. Twenty-seven long-term prospective studies met our inclusion criterias. From the pooled analysis, elevated BNP/NT-proBNP was significantly associated with increased all cause mortality [odds ratio (OR), 3.85; 95% CI, 3.11 to 4.75], cardiovascular mortality (OR, 4.05; 95% CI, 2.53 to 6.84), and cardiovascular events (OR, 7.02; 95% CI, 2.21 to 22.33). The funnel plot showed no evidence of publication bias. The corresponding pooled positive and negative likelihood ratio for prediction of all cause mortality were 1.86 (95% CI, 1.66 to 2.08) and 0.48 (95% CI, 0.42 to 0.55), respectively.
BNP/NT-proBNP is a promising prognostic tool to risk-stratify the patients with ESRD. Further investigations are warranted to elucidate the specific pathogenic mechanisms and the impact of other potential prognostic factors.
Background The extent to which adult height, a biomarker of the interplay of genetic endowment and early-life experiences, is related to risk of chronic diseases in adulthood is uncertain.
Methods We calculated hazard ratios (HRs) for height, assessed in increments of 6.5 cm, using individual–participant data on 174 374 deaths or major non-fatal vascular outcomes recorded among 1 085 949 people in 121 prospective studies.
Results For people born between 1900 and 1960, mean adult height increased 0.5–1 cm with each successive decade of birth. After adjustment for age, sex, smoking and year of birth, HRs per 6.5 cm greater height were 0.97 (95% confidence interval: 0.96–0.99) for death from any cause, 0.94 (0.93–0.96) for death from vascular causes, 1.04 (1.03–1.06) for death from cancer and 0.92 (0.90–0.94) for death from other causes. Height was negatively associated with death from coronary disease, stroke subtypes, heart failure, stomach and oral cancers, chronic obstructive pulmonary disease, mental disorders, liver disease and external causes. In contrast, height was positively associated with death from ruptured aortic aneurysm, pulmonary embolism, melanoma and cancers of the pancreas, endocrine and nervous systems, ovary, breast, prostate, colorectum, blood and lung. HRs per 6.5 cm greater height ranged from 1.26 (1.12–1.42) for risk of melanoma death to 0.84 (0.80–0.89) for risk of death from chronic obstructive pulmonary disease. HRs were not appreciably altered after further adjustment for adiposity, blood pressure, lipids, inflammation biomarkers, diabetes mellitus, alcohol consumption or socio-economic indicators.
Conclusion Adult height has directionally opposing relationships with risk of death from several different major causes of chronic diseases.
Height; cardiovascular disease; cancer; cause-specific mortality; epidemiological study; meta-analysis
To prospectively explore the association between non-high-density lipoprotein cholesterol (non-HDLC) and the risks of stroke and its subtypes.
A total of 95,916 participants (18-98 years old; 76,354 men and 19,562 women) from a Chinese urban community who were free of myocardial infarction and stroke at baseline time point (2006-2007) were eligible and enrolled in the study. The serum non-HDLC levels of participants were determined by subtracting the high-density lipoprotein cholesterol (HDLC) from total serum cholesterol. The primary outcome was the first occurrence of stroke, which was diagnosed according to the World Health Organization criteria and classified into three subtypes: ischemic stroke, intracerebral hemorrhage, or subarachnoid hemorrhage. The Cox proportional hazards models were used to estimate risk of stroke and its subtypes.
During the four-year follow-up, we identified 1614 stroke events (1,156 ischemic, 416 intracerebral hemorrhagic and 42 subarachnoid hemorrhagic). Statistical analyses showed that hazard ratios (HR) (95% Confidence Interval: CI) of serum Non-HDLC level for total and subtypes of stroke were: 1.08 (1.03-1.12) (total), 1.10 (1.05-1.16) (ischemic), 1.03 (0.96-1.10) (intracerebral hemorrhage) and 0.83 (0.66-1.05) (subarachnoid hemorrhage). HR for non-HDLC refers to the increase per each 20 mg/dl. For total and ischemic stroke, the risks were significantly higher in the fourth and fifth quintiles of non-HDLC concentrations compared to the first quintile after adjusting the confounding factors (total stroke: 4th quintile HR=1.33 (1.12-1.59); 5th quintile HR = 1.36 (1.15-1.62); ischemic stroke: 4th quintile HR =1.34 (1.09-1.66); 5th quintile HR = 1.53 (1.24-1.88)).
Our data suggest that serum non-HDLC level is an independent risk factor for total and ischemic stroke, and that higher serum non-HDLC concentrations are associated with increased risks for total stroke and ischemic stroke, but not for intracerebral and subarachnoid hemorrhage.
Breast cancer is the most commonly diagnosed cancer among women worldwide. Many women have become more aware of the benefits of increasing fruit consumption, as part of a healthy lifestyle, for the prevention of cancer. The mechanisms by which fruits, including berries, prevent breast cancer can be partially explained by exploring their interactions with pathways known influence cell-proliferation and evasion of cell-death. Two receptor pathways- estrogen receptor (ER) and tyrosine kinase receptors, especially the epidermal growth factor receptor (EGFR) family- are drivers of cell-proliferation and play a significant role in the development of both primary and recurrent breast cancer. There is strong evidence to show that several phytochemicals present in berries such as cyanidin, delphinidin, quercetin, kaempferol, ellagic acid, resveratrol and pterostilbene, interact with and alter the effects of these pathways. Further, they also induce cell death (apoptosis and autophagy) via their influence on kinase signaling. In this review, we summarize in vitro data regarding the interaction of berry polyphenols with the specific receptors and the mechanisms by which they induce cell death. Further, we also present in vivo data of primary breast cancer prevention by individual compounds and whole berries. Finally, we present a possible role for berries and berry compounds in the prevention of breast cancer and our perspective on the areas that require further research.
Berries; Berry Polyphenols; Breast Cancer; Ellagic Acid; Cyanidin; Delphinidin; Quercetin; Kaempherol; Resveratrol; Estrogen Receptor; Epidermal Growth Factor Receptor; Kinase Signaling; Apoptosis; Autophagy; ACI rats
Many computational methods for identification of transcription regulatory modules often result in many false positives in practice due to noise sources of binding information and gene expression profiling data. In this paper, we propose a multi-level strategy for condition-specific gene regulatory module identification by integrating motif binding information and gene expression data through support vector regression and significant analysis. We have demonstrated the feasibility of the proposed method on a yeast cell cycle data set. The study on a breast cancer microarray data set shows that it can successfully identify the significant and reliable regulatory modules associated with breast cancer.
transcription regulatory module; motif enrichment analysis; SVR; support vector regression; statistical significance analysis; multi-level regulator identification
Genome-wide association studies have shown that variance in the fat mass- and obesity- associated gene (FTO) is associated with risk of obesity in Europeans and Asians. Since obesity is associated with an increased risk of cardiovascular disease (CVD), several studies have investigated the association between variant in the FTO gene and CVD risk, with inconsistent results. In this study, we performed a meta-analysis to clarify the association of rs9939609 variant (or its proxies [r2>0.90]) in the FTO gene with CVD risk.
Published literature from PubMed and Embase was retrieved. Pooled odds ratios with 95% confidence intervals were calculated using the fixed- or random- effects model.
A total of 10 studies (comprising 19,153 CVD cases and 103,720 controls) were included in the meta-analysis. The results indicated that the rs9939609 variant was significantly associated with CVD risk (odds ratio = 1.18, 95% confidence interval = 1.07–1.30, p = 0.001 [Z test], I2 = 80.6%, p<0.001 [heterogeneity]), and there was an insignificant change after adjustment for body mass index (BMI) and other conventional CVD risk factors (odds ratio = 1.16, 95% confidence interval = 1.05–1.27, p = 0.003 [Z test], I2 = 75.4%, p<0.001 [heterogeneity]).
The present meta-analysis confirmed the significant association of the rs9939609 variant in the FTO gene with CVD risk, which was independent of BMI and other conventional CVD risk factors.
Lack of understanding of endocrine resistance remains one of the major challenges for breast cancer researchers, clinicians, and patients. Current reductionist approaches to understanding the molecular signaling driving resistance have offered mostly incremental progress over the past 10 years. As the field of systems biology has begun to mature, the approaches and network modeling tools being developed and applied therein offer a different way to think about how molecular signaling and the regulation of critical cellular functions are integrated. To gain novel insights, we first describe some of the key challenges facing network modeling of endocrine resistance, many of which arise from the properties of the data spaces being studied. We then use activation of the unfolded protein response (UPR) following induction of endoplasmic reticulum stress in breast cancer cells by antiestrogens, to illustrate our approaches to computational modeling. Activation of UPR is a key determinant of cell fate decision making and regulation of autophagy and apoptosis. These initial studies provide insight into a small subnetwork topology obtained using differential dependency network analysis and focused on the UPR gene XBP1. The XBP1 subnetwork topology incorporates BCAR3, BCL2, BIK, NFκB, and other genes as nodes; the connecting edges represent the dependency structures amongst these nodes. As data from ongoing cellular and molecular studies become available, we will build detailed mathematical models of this XBP1-UPR network.
Antiestrogen; autophagy; apoptosis; breast cancer; cell signaling; endoplasmic reticulum; estrogens; gene networks; unfolded protein response; computational modeling; mathematical modeling; systems biology
With the advent of high-throughput biotechnology capable of monitoring genomic signals, it becomes increasingly promising to understand molecular cellular mechanisms through systems biology approaches. One of the active research topics in systems biology is to infer gene transcriptional regulatory networks using various genomic data; this inference problem can be formulated as a linear model with latent signals associated with some regulatory proteins called transcription factors (TFs). As common statistical assumptions may not hold for genomic signals, typical latent variable algorithms such as independent component analysis (ICA) are incapable to reveal underlying true regulatory signals. Liao et al.  proposed to perform inference using an approach named network component analysis (NCA), the optimization of which is achieved by a least-squares fitting approach with biological knowledge constraints. However, the incompleteness of biological knowledge and its inconsistency with gene expression data are not considered in the original NCA solution, which could greatly affect the inference accuracy. To overcome these limitations, we propose a linear extraction scheme, namely regulatory component analysis (RCA), to infer underlying regulatory signals even with partial biological knowledge. Numerical simulations show a significant improvement of our proposed RCA over NCA, not only when signal-to-noise-ratio (SNR) is low, but also when the given biological knowledge is incomplete and inconsistent to gene expression data. Furthermore, real biological experiments on E. coli are performed for regulatory network inference in comparison with several typical linear latent variable methods, which again demonstrates the effectiveness and improved performance of the proposed algorithm.
Transcriptional regulatory network inference; Source extraction; Gene expression; Genomic signal processing
Motivation: Identification of transcriptional regulatory networks (TRNs) is of significant importance in computational biology for cancer research, providing a critical building block to unravel disease pathways. However, existing methods for TRN identification suffer from the inclusion of excessive ‘noise’ in microarray data and false-positives in binding data, especially when applied to human tumor-derived cell line studies. More robust methods that can counteract the imperfection of data sources are therefore needed for reliable identification of TRNs in this context.
Results: In this article, we propose to establish a link between the quality of one target gene to represent its regulator and the uncertainty of its expression to represent other target genes. Specifically, an outlier sum statistic was used to measure the aggregated evidence for regulation events between target genes and their corresponding transcription factors. A Gibbs sampling method was then developed to estimate the marginal distribution of the outlier sum statistic, hence, to uncover underlying regulatory relationships. To evaluate the effectiveness of our proposed method, we compared its performance with that of an existing sampling-based method using both simulation data and yeast cell cycle data. The experimental results show that our method consistently outperforms the competing method in different settings of signal-to-noise ratio and network topology, indicating its robustness for biological applications. Finally, we applied our method to breast cancer cell line data and demonstrated its ability to extract biologically meaningful regulatory modules related to estrogen signaling and action in breast cancer.
Availability and implementation: The Gibbs sampler MATLAB package is freely available at http://www.cbil.ece.vt.edu/software.htm.
Supplementary data are available at Bioinformatics online.
The American Cancer Society estimates that over 200,000 new breast cancer cases are diagnosed annually in the USA alone. Of these cases, the majority are invasive breast cancers and almost 70% are estrogen receptor-α positive. Therapies targeting the estrogen receptor-α are widely applied and include selective estrogen receptor modulators such as tamoxifen, a selective estrogen receptor downregulator such as Fulvestrant (Faslodex; FAS, ICI 182,780), or one of the third-generation aromatase inhibitors including letrozole or anastrozole. While these treatments reduce breast cancer mortality, many estrogen receptor-α-positive tumors eventually recur, highlighting the clinical significance of endocrine therapy resistance. The signaling leading to endocrine therapy resistance is poorly understood; however, preclinical studies have established an important role for autophagy in the acquired resistance phenotype. Autophagy is a cellular degradation process initiated in response to stress or nutrient deprivation, which attempts to restore metabolic homeostasis through the catabolic lysis of aggregated proteins, unfolded/misfolded proteins or damaged subcellular organelles. The duality of autophagy, which can be either pro-survival or pro-death, is well known. However, in the context of endocrine therapy resistance in breast cancer, the inhibition of autophagy can potentiate resensitization of previously antiestrogen resistant breast cancer cells. In this article, we discuss the complex and occasionally contradictory roles of autophagy in cancer and in resistance to endocrine therapies in breast cancer.
3-methyladenine; antiestrogen resistance; aromatase inhibitor; autophagy; bafilomycin A1; breast cancer; endoplasmic reticulum stress; fulvestrant; hydroxychloroquine; tamoxifen; unfolded protein response
Wnt signalling has been implicated in stem cell regulation however its role in breast cancer stem cell regulation remains unclear.
We used a panel of normal and breast cancer cell lines to assess Wnt pathway gene and protein expression, and for the investigation of Wnt signalling within stem cell-enriched populations, mRNA and protein expression was analysed after the selection of anoikis-resistant cells. Finally, cell lines and patient-derived samples were used to investigate Wnt pathway effects on stem cell activity in vitro.
Wnt pathway signalling increased in cancer compared to normal breast and in both cell lines and patient samples, expression of Wnt pathway genes correlated with estrogen receptor (ER) expression. Furthermore, specific Wnt pathway genes were predictive for recurrence within subtypes of breast cancer. Canonical Wnt pathway genes were increased in breast cancer stem cell-enriched populations in comparison to normal breast stem cell-enriched populations. Furthermore in cell lines, the ligand Wnt3a increased whilst the inhibitor DKK1 reduced mammosphere formation with the greatest inhibitory effects observed in ER+ve breast cancer cell lines. In patient-derived metastatic breast cancer samples, only ER-ve mammospheres were responsive to the ligand Wnt3a. However, the inhibitor DKK1 efficiently inhibited both ER+ve and ER-ve breast cancer but not normal mammosphere formation, suggesting that the Wnt pathway is aberrantly activated in breast cancer mammospheres.
Collectively, these data highlight differential Wnt signalling in breast cancer subtypes and activity in patient-derived metastatic cancer stem-like cells indicating a potential for Wnt-targeted treatment in breast cancers.
Developmental stage of rat mammary gland at the time of estrogen exposure determines whether the exposure increases or reduces later breast cancer risk. For example, in utero exposure to 17β-estradiol (E2) increases, whereas prepubertal exposure to this hormone decreases susceptibility of developing carcinogen-induced mammary tumors. E2 mediates its actions by interacting with caveolin-1 (CAV1), a putative tumor suppressor gene in breast cancer. Mammary tissues from 2-month-old rats exposed to E2 in utero contained decreased levels of CAV1, whereas prepubertal E2 exposure increased the levels, when compared to vehicle controls. Low CAV1 expression was associated with increased cell proliferation and estrogen receptor α expression, and reduced apoptosis in the mammary glands of rats exposed to E2 in utero. In contrast, high CAV1 expression correlated with reduced cell proliferation and cyclin D1 and phospho-Akt levels, and increased apoptosis in the mammary glands of rats exposed to E2 during prepuberty. In support of the role of CAV1 as a negative regulator of a variety of pro-growth signaling proteins, we detected decreased levels of Src and ErbB2 in rats exposed to E2 during prepuberty. Thus, estrogen exposure during mammary gland development affects the expression and function of CAV1 in a manner consistent with observed changes in susceptibility to mammary tumorigenesis.
caveolin-1; estradiol; mammary gland
Dietary polyunsaturated fatty acids (PUFA) are inversely related to coronary heart disease (CHD) in epidemiological studies. We examined the associations of plasma n-6 and n-3 PUFA in cholesteryl esters with fatal CHD in a nested case-control study. Additionally, we performed a dose-response meta-analysis of similar prospective studies on cholesteryl ester PUFA.
We used data from two population-based cohort studies in Dutch adults aged 20–65y. Blood and data collection took place from 1987–1997 and subjects were followed for 8–19y. We identified 279 incident cases of fatal CHD and randomly selected 279 controls, matched on age, gender, and enrollment date. Odds ratios (OR) were calculated per standard deviation (SD) increase of cholesteryl ester PUFA.
After adjustment for confounders, the OR (95%CI) for fatal CHD per SD increase in plasma linoleic acid was 0.89 (0.74–1.06). Additional adjustment for plasma total cholesterol and systolic blood pressure attenuated this association (OR:0.95; 95%CI: 0.78–1.15). Arachidonic acid was not associated with fatal CHD (OR per SD:1.11; 95%CI: 0.92–1.35). The ORs (95%CI) for fatal CHD for an SD increase in n-3 PUFA were 0.92 (0.74–1.15) for alpha-linolenic acid and 1.06 (0.88–1.27) for EPA-DHA. In the meta-analysis, a 5% higher linoleic acid level was associated with a 9% lower risk (relative risk: 0.91; 95% CI: 0.84–0.98) of CHD. The other fatty acids were not associated with CHD.
In this Dutch population, n-6 and n-3 PUFA in cholesteryl esters were not significantly related to fatal CHD. Our data, together with findings from previous prospective studies, support that linoleic acid in plasma cholesteryl is inversely associated with CHD.
The majority of estrogen receptor (ER)-positive breast cancers are treated with endocrine therapy. While this is effective, acquired resistance to therapies targeted against ER is a major clinical challenge. Here, model systems of ER-positive breast cancers with differential susceptibility to endocrine therapy were employed to define common nodes for new therapeutic interventions. These analyses revealed that cell cycle progression is effectively uncoupled from the activity and functional state of ER in these models. In this context, cyclin D1 expression and retinoblastoma tumor suppressor protein (RB) phosphorylation are maintained even with efficient ablation of ER with pure antagonists. These therapy-resistant models recapitulate a key feature of deregulated RB/E2F transcriptional control. Correspondingly, a gene expression signature of RB-dysfunction is associated with luminal B breast cancer, which exhibits a relatively poor response to endocrine therapy. These collective findings suggest that suppression of cyclin D-supported kinase activity and restoration of RB-mediated transcriptional repression could represent a viable therapeutic option in tumors that fail to respond to hormone-based therapies. Consistent with this hypothesis, a highly selective CDK4/6 inhibitor, PD-0332991, was effective at suppressing the proliferation of all hormone refractory models analyzed. Importantly, PD-0332991 led to a stable cell cycle arrest that was fundamentally distinct from those elicited by ER antagonists, and was capable of inducing aspects of cellular senescence in hormone therapy refractory cell populations. These findings underscore the clinical utility of downstream cytostatic therapies in treating tumors that have experienced failure of endocrine therapy.
Coronary heart disease (CHD) remains a major public health burden, causing 80,000 deaths annually in England and Wales, with major inequalities. However, there are no recent analyses of age-specific socioeconomic trends in mortality. We analysed annual trends in inequalities in age-specific CHD mortality rates in small areas in England, grouped into deprivation quintiles.
We calculated CHD mortality rates for 10-year age groups (from 35 to ≥85 years) using three year moving averages between 1982 and 2006. We used Joinpoint regression to identify significant turning points in age- sex- and deprivation-specific time trends. We also analysed trends in absolute and relative inequalities in age-standardised rates between the least and most deprived areas.
Between 1982 and 2006, CHD mortality fell by 62.2% in men and 59.7% in women. Falls were largest for the most deprived areas with the highest initial level of CHD mortality. However, a social gradient in the pace of fall was apparent, being steepest in the least deprived quintile. Thus, while absolute inequalities narrowed over the period, relative inequalities increased. From 2000, declines in mortality rates slowed or levelled off in the youngest groups, notably in women aged 45–54 in the least deprived groups. In contrast, from age 55 years and older, rates of fall in CHD mortality accelerated in the 2000s, likewise falling fastest in the least deprived quintile.
Age-standardised CHD mortality rates have declined substantially in England, with the steepest falls in the most affluent quintiles. However, this concealed contrasting patterns in underlying age-specific rates. From 2000, mortality rates levelled off in the youngest groups but accelerated in middle aged and older groups. Mortality analyses by small areas could provide potentially valuable insights into possible drivers of inequalities, and thus inform future strategies to reduce CHD mortality across all social groups.
Background and Objectives
Hypertension represents a major cause of cardiovascular morbidity and mortality worldwide but its prevalence has been shown to vary in different countries. The reasons for such differences are still matter of debate, the relative contributions given by environmental and genetic factors being still poorly defined. We estimated the current prevalence, distribution and determinants of hypertension in isolated Sardinian populations and also investigated the environmental and genetic contribution to hypertension prevalence taking advantage of the characteristics of such populations.
Methods and Results
An epidemiological survey with cross-sectional design was carried out measuring blood pressure in 9845 inhabitants of 10 villages of Ogliastra region between 2002 and 2008. Regression analysis for assessing blood pressure determinants and variance component models for estimating heritability were performed. Overall 38.8% of this population had hypertension, its prevalence varying significantly by age, sex and among villages taking into account age and sex structure of their population. About 50% of hypertensives had prior cardiovascular disease. High blood pressure was independently associated with age, obesity related factors, heart rate, total cholesterol, alcohol consumption, low education and smoking status, all these factors contributing more in women than in men. Heritability was 27% for diastolic and 36% for systolic blood pressure, its contribution being significantly higher in men (57%) than in women (46%). Finally, the genetic correlation between systolic and diastolic blood pressure was 0.74, indicating incomplete pleiotropy.
Genetic factors involved in the expression of blood pressure traits account for about 30% of the phenotypic variance, but seem to play a larger role in men; comorbidities and environmental factors remain of predominant importance, but seem to contribute much more in women.
How breast cancer cells respond to the stress of endocrine therapies determines whether they acquire a resistant phenotype or execute a cell death pathway. A successfully executed survival signal then requires determination of whether or not to replicate. How these cell fate decisions are regulated is unclear but evidence suggests that the signals determining these outcomes are highly integrated. Central to the final cell fate decision is signaling from the unfolded protein response, which can be activated following the sensing of stress within the endoplasmic reticulum. Duration of the response to stress is partly mediated by the duration of inositol requiring enzyme-1 (IRE1; ERN) activation following its release from heat shock protein A5 (HSPA5). The resulting signaling appears to use several B-cell lymphoma-2 (BCL2) family members to both suppress apoptosis and activate autophagy. Changes in metabolism induced by cellular stress are key components of this regulatory system, and further adaptation of the metabolome is affected in response to stress. Here we describe the unfolded protein response, autophagy and apoptosis, and how their regulation is integrated. Central topological features of the signaling network that integrate cell fate regulation and decision execution are discussed.
Cell signaling; endoplasmic reticulum; estrogens; unfolded protein response
Although oestrogen is essential for the development of the normal breast, adult mammary stem cells are known to be oestrogen receptor alpha (ER) negative and rely on paracrine signals in the mammary epithelium for mediation of developmental cues. However, little is known about how systemic oestrogen regulates breast cancer stem cell (CSC) activity.
Here, we tested the effects of oestrogen on CSC activity in vitro and in vivo and investigated which paracrine signalling pathways locally mediate oestrogen effects.
CSC-enriched populations (ESA+CD44+CD24low) sorted from ER positive patient derived and established cell lines have low or absent ER expression. However, oestrogen stimulated CSC activity demonstrated by increased mammosphere and holoclone formation in vitro and tumour formation in vivo. This effect was abrogated by the anti-oestrogen tamoxifen or ER siRNA. These data suggest that the oestrogen response is mediated through paracrine signalling from non-CSCs to CSCs. We have, therefore, investigated both epidermal growth factor (EGF) and Notch receptor signals downstream of oestrogen. We demonstrate that gefitinib (epidermal growth factor receptor (EGFR) inhibitor) and gamma secretase inhibitors (Notch inhibitor) block oestrogen-induced CSC activity in vitro and in vivo but GSIs more efficiently reduce CSC frequency.
These data establish that EGF and Notch receptor signalling pathways operate downstream of oestrogen in the regulation of ER negative CSCs.
While more than 70% of breast cancers express estrogen receptor-α (ER+), endocrine therapies targeting these receptors often fail. The molecular mechanisms that underlie treatment resistance remain unclear. We investigated the potential role of glucose-regulated protein 78 (GRP78) in mediating estrogen resistance. Human breast tumors showed increased GRP78 expression when compared with normal breast tissues. However, GRP78 expression was reduced in ER+ breast tumors compared with HER2-amplifed or triple-negative breast tumors. ER+ antiestrogen-resistant cells and ER+ tumors with an acquired resistant antiestrogen phenotype were both shown to overexpress GRP78, which was not observed in cases of de novo resistance. Knockdown of GRP78 restored antiestrogen sensitivity in resistant cells, and overexpression of GRP78 promoted resistance in sensitive cells. Mechanistically, GRP78 integrated multiple cellular signaling pathways to inhibit apoptosis and stimulate prosurvival autophagy, which was dependent on TSC2/AMPK-mediated mTOR inhibition but not on beclin-1. Inhibition of autophagy prevented GRP78-mediated endocrine resistance, whereas caspase inhibition abrogated the resensitization that resulted from GRP78 loss. Simultaneous knockdown of GRP78 and beclin-1 synergistically restored antiestrogen sensitivity in resistant cells. Together, our findings reveal a novel role for GRP78 in the integration of cellular signaling pathways including the unfolded protein response, apoptosis, and autophagy to determine cell fate in response to antiestrogen therapy.
Pathways involved in DCIS stem and progenitor signalling are poorly understood yet are critical to understand DCIS biology and to develop new therapies. Notch and ErbB1/2 receptor signalling cross talk has been demonstrated in invasive breast cancer, but their role in DCIS stem and progenitor cells has not been investigated. We have utilised 2 DCIS cell lines, MCF10DCIS.com (ErbB2-normal) and SUM225 (ErbB2-overexpressing) and 7 human primary DCIS samples were cultured in 3D matrigel and as mammospheres in the presence, absence or combination of the Notch inhibitor, DAPT, and ErbB1/2 inhibitors, lapatinib or gefitinib. Western blotting was applied to assess downstream signalling. In this study we demonstrate that DAPT reduced acini size and mammosphere formation in MCF10DCIS.com whereas there was no effect in SUM225. Lapatinb reduced acini size and mammosphere formation in SUM225, whereas mammosphere formation and Notch1 activity were increased in MCF10DCIS.com. Combined DAPT/lapatinib treatment was more effective at reducing acini size in both DCIS cell lines. Mammosphere formation in cell lines and human primary DCIS was reduced further by DAPT/lapatinib or DAPT/gefitinib regardless of ErbB2 receptor status. Our pre-clinical human models of DCIS demonstrate that Notch and ErbB1/2 both play a role in DCIS acini growth and stem cell activity. We report for the first time that cross talk between the two pathways in DCIS occurs regardless of ErbB2 receptor status and inhibition of Notch and ErbB1/2 was more efficacious than either alone. These data provide further understanding of DCIS biology and suggest treatment strategies combining Notch and ErbB1/2 inhibitors should be investigated regardless of ErbB2 receptor status.