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
Background and Purpose
Ischemic stroke (IS) and coronary artery disease (CAD) share several risk factors and each have a substantial heritability. We conducted a genome-wide analysis to evaluate the extent of shared genetic determination of the two diseases.
Genome-wide association data were obtained from the METASTROKE, CARDIoGRAM, and C4D consortia. We first analyzed common variants reaching a nominal threshold of significance (p<0.01) for CAD for their association with IS and vice versa. We then examined specific overlap across phenotypes for variants that reached a high threshold of significance. Finally, we conducted a joint meta-analysis on the combined phenotype of IS or CAD. Corresponding analyses were performed restricted to the 2,167 individuals with the ischemic large artery stroke (LAS) subtype.
Common variants associated with CAD at p<0.01 were associated with a significant excess risk for IS and for LAS and vice versa. Among the 42 known genome-wide significant loci for CAD, three and five loci were significantly associated with IS and LAS, respectively. In the joint meta-analyses, 15 loci passed genome-wide significance (p<5×10-8) for the combined phenotype of IS or CAD and 17 loci passed genome-wide significance for LAS or CAD. Since these loci had prior evidence for genome-wide significance for CAD we specifically analyzed the respective signals for IS and LAS and found evidence for association at chr12q24/SH2B3 (pIS=1.62×10-07) and ABO (pIS =2.6×10-4) as well as at HDAC9 (pLAS=2.32×10-12), 9p21 (pLAS =3.70×10-6), RAI1-PEMT-RASD1 (pLAS =2.69×10-5), EDNRA (pLAS =7.29×10-4), and CYP17A1-CNNM2-NT5C2 (pLAS =4.9×10-4).
Our results demonstrate substantial overlap in the genetic risk of ischemic stroke and particularly the large artery stroke subtype with coronary artery disease.
Plasma fibrinogen is an acute phase protein playing an important role in the blood coagulation cascade having strong associations with smoking, alcohol consumption and body mass index (BMI). Genome-wide association studies (GWAS) have identified a variety of gene regions associated with elevated plasma fibrinogen concentrations. However, little is yet known about how associations between environmental factors and fibrinogen might be modified by genetic variation. Therefore, we conducted large-scale meta-analyses of genome-wide interaction studies to identify possible interactions of genetic variants and smoking status, alcohol consumption or BMI on fibrinogen concentration. The present study included 80,607 subjects of European ancestry from 22 studies. Genome-wide interaction analyses were performed separately in each study for about 2.6 million single nucleotide polymorphisms (SNPs) across the 22 autosomal chromosomes. For each SNP and risk factor, we performed a linear regression under an additive genetic model including an interaction term between SNP and risk factor. Interaction estimates were meta-analysed using a fixed-effects model. No genome-wide significant interaction with smoking status, alcohol consumption or BMI was observed in the meta-analyses. The most suggestive interaction was found for smoking and rs10519203, located in the LOC123688 region on chromosome 15, with a p value of 6.2×10−8. This large genome-wide interaction study including 80,607 participants found no strong evidence of interaction between genetic variants and smoking status, alcohol consumption or BMI on fibrinogen concentrations. Further studies are needed to yield deeper insight in the interplay between environmental factors and gene variants on the regulation of fibrinogen concentrations.
With the existence of biologically distinctive malignant cells originated within the same tumor, intratumor functional heterogeneity is present in many cancers and is often manifested by the intermingled vascular compartments with distinct pharmacokinetics. However, intratumor vascular heterogeneity cannot be resolved directly by most in vivo dynamic imaging. We developed multi-tissue compartment modeling (MTCM), a completely unsupervised method of deconvoluting dynamic imaging series from heterogeneous tumors that can improve vascular characterization in many biological contexts. Applying MTCM to dynamic contrast-enhanced magnetic resonance imaging of breast cancers revealed characteristic intratumor vascular heterogeneity and therapeutic responses that were otherwise undetectable. MTCM is readily applicable to other dynamic imaging modalities for studying intratumor functional and phenotypic heterogeneity, together with a variety of foreseeable applications in the clinic.
About 70% of all breast cancers are estrogen receptor alpha positive (ER+) and are treated with antiestrogens. However, 50% of ER + tumors develop resistance to these drugs (endocrine resistance). In endocrine resistant cells, an adaptive pathway called the unfolded protein response (UPR) is elevated that allows cells to tolerate stress more efficiently than in sensitive cells. While the precise mechanism remains unclear, the UPR can trigger both pro-survival and pro-death outcomes that depend on the nature and magnitude of the stress. In this study, we identified MYC, an oncoprotein that is upregulated in endocrine resistant breast cancer, as a regulator of the UPR in glucose-deprived conditions.
ER+ human breast cancer cell lines (LCC1, LCC1, LY2 and LCC9) and rat mammary tumors were used to confirm upregulation of MYC in endocrine resistance. To evaluate functional relevance of proteins, siRNA-mediated inhibition or small molecule inhibitors were used. Cell density/number was evaluated with crystal violet assay; cell cycle and apoptosis were measured by flow cytometry. Relative quantification of glutamine metabolites were determined by mass spectrometry. Signaling molecules of the UPR, apoptosis or autophagy pathways were investigated by western blotting.
Increased MYC function in resistant cells correlated with increased dependency on glutamine and glucose for survival. Inhibition of MYC reduced cell growth and uptake of both glucose and glutamine in resistant cells. Interestingly, in glucose-deprived conditions, glutamine induced apoptosis and necrosis, arrested autophagy, and triggered the unfolded protein response (UPR) though GRP78-IRE1α with two possible outcomes: (i) inhibition of cell growth by JNK activation in most cells and, (ii) promotion of cell growth by spliced XBP1 in the minority of cells. These disparate effects are regulated, at different signaling junctions, by MYC more robustly in resistant cells.
Endocrine resistant cells overexpress MYC and are better adapted to withstand periods of glucose deprivation and can use glutamine in the short term to maintain adequate metabolism to support cell survival. Our findings reveal a unique role for MYC in regulating cell fate through the UPR, and suggest that targeting glutamine metabolism may be a novel strategy in endocrine resistant breast cancer.
Breast cancer; Antiestrogen resistance; Metabolism; Glutamine; Glucose; MYC; Unfolded protein response
Breast cancer cells develop resistance to endocrine therapies by shifting between estrogen receptor (ER)-regulated and growth factor receptor (GFR)-regulated survival signaling pathways. To study this switch, we propose a mathematical model of crosstalk between these pathways. The model explains why MCF7 sub-clones transfected with HER2 or EGFR show three GFR-distribution patterns, and why the bimodal distribution pattern can be reversibly modulated by estrogen. The model illustrates how transient overexpression of ER activates GFR signaling and promotes estrogen-independent growth. Understanding this survival-signaling switch can help in the design of future therapies to overcome resistance in breast cancer.
Mathematical modeling; Estrogen receptor signaling; Growth factor receptor signaling; Breast cancer; Endocrine resistance
Breast cancer is an increasing public health problem. Substantial advances have been made in the treatment of breast cancer, but the introduction of methods to predict women at elevated risk and prevent the disease has been less successful. Here, we summarize recent data on newer approaches to risk prediction, available approaches to prevention, how new approaches may be made, and the difficult problem of using what we already know to prevent breast cancer in populations. During 2012, the Breast Cancer Campaign facilitated a series of workshops, each covering a specialty area of breast cancer to identify gaps in our knowledge. The risk-and-prevention panel involved in this exercise was asked to expand and update its report and review recent relevant peer-reviewed literature. The enlarged position paper presented here highlights the key gaps in risk-and-prevention research that were identified, together with recommendations for action. The panel estimated from the relevant literature that potentially 50% of breast cancer could be prevented in the subgroup of women at high and moderate risk of breast cancer by using current chemoprevention (tamoxifen, raloxifene, exemestane, and anastrozole) and that, in all women, lifestyle measures, including weight control, exercise, and moderating alcohol intake, could reduce breast cancer risk by about 30%. Risk may be estimated by standard models potentially with the addition of, for example, mammographic density and appropriate single-nucleotide polymorphisms. This review expands on four areas: (a) the prediction of breast cancer risk, (b) the evidence for the effectiveness of preventive therapy and lifestyle approaches to prevention, (c) how understanding the biology of the breast may lead to new targets for prevention, and (d) a summary of published guidelines for preventive approaches and measures required for their implementation. We hope that efforts to fill these and other gaps will lead to considerable advances in our efforts to predict risk and prevent breast cancer over the next 10 years.
Estimates of the heritability of plasma fibrinogen concentration, an established predictor of cardiovascular disease (CVD), range from 34 to 50%. Genetic variants so far identified by genome-wide association (GWA) studies only explain a small proportion (< 2%) of its variation.
Methods and Results
We conducted a meta-analysis of 28 GWA studies, including more than 90,000 subjects of European ancestry, the first GWA meta-analysis of fibrinogen levels in 7 African Americans studies totaling 8,289 samples, and a GWA study in Hispanic-Americans totaling 1,366 samples. Evaluation for association of SNPs with clinical outcomes included a total of 40,695 cases and 85,582 controls for coronary artery disease (CAD), 4,752 cases and 24,030 controls for stroke, and 3,208 cases and 46,167 controls for venous thromboembolism (VTE). Overall, we identified 24 genome-wide significant (P<5×10−8) independent signals in 23 loci, including 15 novel associations, together accounting for 3.7% of plasma fibrinogen variation. Gene-set enrichment analysis highlighted key roles in fibrinogen regulation for the three structural fibrinogen genes and pathways related to inflammation, adipocytokines and thyrotrophin-releasing hormone signaling. Whereas lead SNPs in a few loci were significantly associated with CAD, the combined effect of all 24 fibrinogen-associated lead SNPs was not significant for CAD, stroke or VTE.
We identify 23 robustly associated fibrinogen loci, 15 of which are new. Clinical outcome analysis of these loci does not support a causal relationship between circulating levels of fibrinogen and CAD, stroke or VTE.
Fibrinogen; cardiovascular disease; genome-wide association study
Recent advances in RNA sequencing (RNA-Seq) technology have offered unprecedented scope and resolution for transcriptome analysis. However, precise quantification of mRNA abundance and identification of differentially expressed genes are complicated due to biological and technical variations in RNA-Seq data.
We systematically study the variation in count data and dissect the sources of variation into between-sample variation and within-sample variation. A novel Bayesian framework is developed for joint estimate of gene level mRNA abundance and differential state, which models the intrinsic variability in RNA-Seq to improve the estimation. Specifically, a Poisson-Lognormal model is incorporated into the Bayesian framework to model within-sample variation; a Gamma-Gamma model is then used to model between-sample variation, which accounts for over-dispersion of read counts among multiple samples. Simulation studies, where sequencing counts are synthesized based on parameters learned from real datasets, have demonstrated the advantage of the proposed method in both quantification of mRNA abundance and identification of differentially expressed genes. Moreover, performance comparison on data from the Sequencing Quality Control (SEQC) Project with ERCC spike-in controls has shown that the proposed method outperforms existing RNA-Seq methods in differential analysis. Application on breast cancer dataset has further illustrated that the proposed Bayesian model can 'blindly' estimate sources of variation caused by sequencing biases.
We have developed a novel Bayesian hierarchical approach to investigate within-sample and between-sample variations in RNA-Seq data. Simulation and real data applications have validated desirable performance of the proposed method. The software package is available at http://www.cbil.ece.vt.edu/software.htm.
Migration, proliferation and stem cell-like activity are all key cellular characteristics which aid the formation and progression of breast cancer, in addition to involvement in treatment resistance. Many current therapies aim to target tumour proliferation, and although successful, mortality rates in breast cancer remain significant. Our main objectives were to investigate the relationship between proliferation, migration and stem cell-like activity in breast cancer.
We used a panel of cell lines and primary human breast cancer samples to assess the relationship between migration, proliferation and stem cells. We performed live cell sorting according to cell cycle (Hoechst-33324) and in combination with stem-cell markers (CD44/CD24/ESA) followed by assessment of migration and stem cell activity (mammosphere formation).
We identified an inverse relationship between proliferation and migration/stem cell-like activity. G0/1 cells showed increased migration and mammosphere formation. Furthermore we identified a subpopulation of low proliferative stem-like cells (CD44+/24lo/ESA+) with increased migration and mammosphere formation that are specifically inhibited by Dickkopf 1 (DKK1) and Dibenzazepine (DBZ) known stem-cell inhibitors.
These data show the co-ordination of migration, proliferation and stem cell activity in breast cancer, and has identified a sub-population of stem-like cells, greatly adding to our understanding of the complex nature of stem cell biology.
Breast Cancer; Cellular proliferation; Cell migration; Cancer Stem cells
To perform a genome-wide association study (GWAS) using the Immunochip array in 3,420 cases of ischemic stroke and 6,821 controls, followed by a meta-analysis with data from more than 14,000 additional ischemic stroke cases.
Using the Immunochip, we genotyped 3,420 ischemic stroke cases and 6,821 controls. After imputation we meta-analyzed the results with imputed GWAS data from 3,548 cases and 5,972 controls recruited from the ischemic stroke WTCCC2 study, and with summary statistics from a further 8,480 cases and 56,032 controls in the METASTROKE consortium. A final in silico “look-up” of 2 single nucleotide polymorphisms in 2,522 cases and 1,899 controls was performed. Associations were also examined in 1,088 cases with intracerebral hemorrhage and 1,102 controls.
In an overall analysis of 17,970 cases of ischemic stroke and 70,764 controls, we identified a novel association on chromosome 12q24 (rs10744777, odds ratio [OR] 1.10 [1.07–1.13], p = 7.12 × 10−11) with ischemic stroke. The association was with all ischemic stroke rather than an individual stroke subtype, with similar effect sizes seen in different stroke subtypes. There was no association with intracerebral hemorrhage (OR 1.03 [0.90–1.17], p = 0.695).
Our results show, for the first time, a genetic risk locus associated with ischemic stroke as a whole, rather than in a subtype-specific manner. This finding was not associated with intracerebral hemorrhage.
Understanding the origins of resistance to anti-oestrogen drugs is of critical importance to many breast cancer patients. Recent experiments show that knockdown of GRP78, a key gene in the unfolded protein response (UPR), can re-sensitize resistant cells to anti-oestrogens, and overexpression of GRP78 in sensitive cells can cause them to become resistant. These results appear to arise from the operation and interaction of three cellular systems: the UPR, autophagy and apoptosis. To determine whether our current mechanistic understanding of these systems is sufficient to explain the experimental results, we built a mathematical model of the three systems and their interactions. We show that the model is capable of reproducing previously published experimental results and some new data gathered specifically for this paper. The model provides us with a tool to better understand the interactions that bring about anti-oestrogen resistance and the effects of GRP78 on both sensitive and resistant breast cancer cells.
anti-oestrogen resistance; breast cancer; mathematical modelling; GRP78; unfolded protein response; autophagy
Cyclin D1 and its binding partners CDK4/6 are essential regulators of cell cycle progression and are implicated in cancer progression. Our aim was to investigate a potential regulatory role of these proteins in other essential tumor biological characteristics. Using a panel of breast cancer cell lines and primary human breast cancer samples, we have demonstrated the importance of these cell cycle regulators in both migration and stem-like cell activity. siRNA was used to target cyclin D1 and CDK4/6 expression, having opposing effects on both migration and stem-like cell activity dependent upon estrogen receptor (ER) expression. Inhibition of cyclin D1 or CDK4/6 increases or decreases migration and stem-like cell activity in ER−ve (ER-negative) and ER+ve (ER-positive) breast cancer, respectively. Furthermore, overexpressed cyclin D1 caused decreased migration and stem-like cell activity in ER−ve cells while increasing activity in ER+ve breast cancer cells. Treatment of breast cancer cells with inhibitors of cyclin D1 and CDK4/6 (Flavopiridol/PD0332991), currently in clinical trials, mimicked the effects observed with siRNA treatment. Re-expression of ER in two ER−ve cell lines was sufficient to overcome the effects of either siRNA or clinical inhibitors of cyclin D1 and CDK4/6.
In conclusion, cyclin D1 and CDK4/6 have alternate roles in regulation of migration and stem-like cell activity. Furthermore, these effects are highly dependent upon expression of ER. The significance of these results adds to our general understanding of cancer biology but, most importantly, could be used diagnostically to predict treatment response to cell cycle inhibition in breast cancer.
cell cycle; breast cancer; stem cell; migration; estrogen receptor
Modeling biological networks serves as both a major goal and an effective tool of systems biology in studying mechanisms that orchestrate the activities of gene products in cells. Biological networks are context-specific and dynamic in nature. To systematically characterize the selectively activated regulatory components and mechanisms, modeling tools must be able to effectively distinguish significant rewiring from random background fluctuations. While differential networks cannot be constructed by existing knowledge alone, novel incorporation of prior knowledge into data-driven approaches can improve the robustness and biological relevance of network inference. However, the major unresolved roadblocks include: big solution space but a small sample size; highly complex networks; imperfect prior knowledge; missing significance assessment; and heuristic structural parameter learning.
To address these challenges, we formulated the inference of differential dependency networks that incorporate both conditional data and prior knowledge as a convex optimization problem, and developed an efficient learning algorithm to jointly infer the conserved biological network and the significant rewiring across different conditions. We used a novel sampling scheme to estimate the expected error rate due to “random” knowledge. Based on that scheme, we developed a strategy that fully exploits the benefit of this data-knowledge integrated approach. We demonstrated and validated the principle and performance of our method using synthetic datasets. We then applied our method to yeast cell line and breast cancer microarray data and obtained biologically plausible results. The open-source R software package and the experimental data are freely available at http://www.cbil.ece.vt.edu/software.htm.
Experiments on both synthetic and real data demonstrate the effectiveness of the knowledge-fused differential dependency network in revealing the statistically significant rewiring in biological networks. The method efficiently leverages data-driven evidence and existing biological knowledge while remaining robust to the false positive edges in the prior knowledge. The identified network rewiring events are supported by previous studies in the literature and also provide new mechanistic insight into the biological systems. We expect the knowledge-fused differential dependency network analysis, together with the open-source R package, to be an important and useful bioinformatics tool in biological network analyses.
Biological networks; Probabilistic graphical models; Differential dependency network; Network rewiring; Network analysis; Systems biology; Knowledge incorporation; Convex optimization
Background: Elevated plasma homocysteine is a risk factor for Alzheimer disease, but the relevance of homocysteine lowering to slow the rate of cognitive aging is uncertain.
Objective: The aim was to assess the effects of treatment with B vitamins compared with placebo, when administered for several years, on composite domains of cognitive function, global cognitive function, and cognitive aging.
Design: A meta-analysis was conducted by using data combined from 11 large trials in 22,000 participants. Domain-based z scores (for memory, speed, and executive function and a domain-composite score for global cognitive function) were available before and after treatment (mean duration: 2.3 y) in the 4 cognitive-domain trials (1340 individuals); Mini-Mental State Examination (MMSE)–type tests were available at the end of treatment (mean duration: 5 y) in the 7 global cognition trials (20,431 individuals).
Results: The domain-composite and MMSE-type global cognitive function z scores both decreased with age (mean ± SE: −0.054 ± 0.004 and −0.036 ± 0.001/y, respectively). Allocation to B vitamins lowered homocysteine concentrations by 28% in the cognitive-domain trials but had no significant effects on the z score differences from baseline for individual domains or for global cognitive function (z score difference: 0.00; 95% CI: −0.05, 0.06). Likewise, allocation to B vitamins lowered homocysteine by 26% in the global cognition trials but also had no significant effect on end-treatment MMSE-type global cognitive function (z score difference: −0.01; 95% CI: −0.03, 0.02). Overall, the effect of a 25% reduction in homocysteine equated to 0.02 y (95% CI: −0.10, 0.13 y) of cognitive aging per year and excluded reductions of >1 mo per year of treatment.
Conclusion: Homocysteine lowering by using B vitamins had no significant effect on individual cognitive domains or global cognitive function or on cognitive aging.
Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 m genotypes from 25,580 Alzheimer's cases and 48,466 controls.
In addition to earlier reported genes, we detected genome-wide significant loci on chromosomes 8 (TP53INP1, p = 1.4×10−6) and 14 (IGHV1-67 p = 7.9×10−8) which indexed novel susceptibility loci.
The additional genes identified in this study, have an array of functions previously implicated in Alzheimer's disease, including aspects of energy metabolism, protein degradation and the immune system and add further weight to these pathways as potential therapeutic targets in Alzheimer's disease.
Eleven susceptibility loci for late-onset Alzheimer’s disease (LOAD) were identified by previous studies; however, a large portion of the genetic risk for this disease remains unexplained. We conducted a large, two-stage meta-analysis of genome-wide association studies (GWAS) in individuals of European ancestry. In stage 1, we used genotyped and imputed data (7,055,881 SNPs) to perform meta-analysis on 4 previously published GWAS data sets consisting of 17,008 Alzheimer’s disease cases and 37,154 controls. In stage 2,11,632 SNPs were genotyped and tested for association in an independent set of 8,572 Alzheimer’s disease cases and 11,312 controls. In addition to the APOE locus (encoding apolipoprotein E), 19 loci reached genome-wide significance (P < 5 × 10−8) in the combined stage 1 and stage 2 analysis, of which 11 are newly associated with Alzheimer’s disease.
Endocrine therapies targeting cell proliferation and survival mediated by estrogen receptor α (ERα) are among the most effective systemic treatments for ERα-positive breast cancer. However, most tumors initially responsive to these therapies acquire resistance through mechanisms that involve ERα transcriptional regulatory plasticity. Herein we identify VAV3 as a critical component in this process.
A cell-based chemical compound screen was carried out to identify therapeutic strategies against resistance to endocrine therapy. Binding to ERα was evaluated by molecular docking analyses, an agonist fluoligand assay and short hairpin (sh)RNA–mediated protein depletion. Microarray analyses were performed to identify altered gene expression. Western blot analysis of signaling and proliferation markers, and shRNA-mediated protein depletion in viability and clonogenic assays, were performed to delineate the role of VAV3. Genetic variation in VAV3 was assessed for association with the response to tamoxifen. Immunohistochemical analyses of VAV3 were carried out to determine its association with therapeutic response and different tumor markers. An analysis of gene expression association with drug sensitivity was carried out to identify a potential therapeutic approach based on differential VAV3 expression.
The compound YC-1 was found to comparatively reduce the viability of cell models of acquired resistance. This effect was probably not due to activation of its canonical target (soluble guanylyl cyclase), but instead was likely a result of binding to ERα. VAV3 was selectively reduced upon exposure to YC-1 or ERα depletion, and, accordingly, VAV3 depletion comparatively reduced the viability of cell models of acquired resistance. In the clinical scenario, germline variation in VAV3 was associated with the response to tamoxifen in Japanese breast cancer patients (rs10494071 combined P value = 8.4 × 10−4). The allele association combined with gene expression analyses indicated that low VAV3 expression predicts better clinical outcome. Conversely, high nuclear VAV3 expression in tumor cells was associated with poorer endocrine therapy response. Based on VAV3 expression levels and the response to erlotinib in cancer cell lines, targeting EGFR signaling may be a promising therapeutic strategy.
This study proposes VAV3 as a biomarker and a rationale for its use as a signaling target to prevent and/or overcome resistance to endocrine therapy in breast cancer.
Although targeted therapies against HER2 have been one of the most successful therapeutic strategies for breast cancer, patients eventually developed acquired resistance from compensatory upregulation of alternate HERs and mitogen-activated protein kinase–phosphoinositide 3-kinase (PI3K)/Akt/mTOR signaling. As we and others have shown that the soluble ectodomain fragment of E-cadherin exerts prooncogenic effects via HER1/2–mediated binding and activation of downstream prosurvival pathways, we explored whether targeting this ectodomain [DECMA-1 monoclonal antibody (mAb)] was effective in the treatment of HER2-positive (HER2+) breast cancers.
MMTV-PyMT transgenic mice and HER2+/E-cadherin–positive MCF-7 and BT474 trastuzumab-resistant (TtzmR) cells were treated with the DECMA-1 mAb. Antitumor responses were assessed by bromodeoxyuridine incorporation, apoptosis, and necrosis. The underlying intracellular prooncogenic pathways were explored using subcellular fractionation, immunoprecipitation, fluorescence microscopy, and immunoblotting.
Treatment with DECMA-1 mAb significantly delayed tumor onset and attenuated tumor burden in MMTV-PyMT mice by reducing tumor cell proliferation and inducing apoptosis without any detectable cytotoxicity to mice or end-organs. In vitro treatment of MCF-7 and BT474 TtzmR cells reduced proliferation and induced cancer cell apoptosis. Importantly, this inhibition of breast tumorigenesis was due to concomitant downregulation, via ubiquitin-mediated degradation through the lysosome and proteasome pathways, of all HER family members, components of downstream PI3K/Akt/mTOR prosurvival signaling and suppression of inhibitor of apoptosis proteins.
Our results establish that the E-cadherin ectodomain-specific mAb DECMA-1 inhibits Ecad+/HER2+ breast cancers by hindering tumor growth and inducing apoptosis via downregulation of key oncogenic pathways involved in trastuzumab resistance, thereby establishing a novel therapeutic platform for the treatment of HER2+ breast cancers.
A significant proportion of the genes regulated by 17-beta-estradiol (E2) via estrogen receptor alpha (ERα) have roles in vesicle trafficking in breast cancer. Intracellular vesicle trafficking and extracellular vesicles have important roles in tumourigenesis. Here we report the discovery of giant (3-42μm) intracellular and extracellular vesicles (GVs) and the role of E2 on vesicle formation in breast cancer (BC) cell lines using three independent live cell imaging techniques. Large diameter vesicles, GVs were also identified in a patient-derived xenograft BC model, and in invasive breast carcinoma tissue. ERα-positive (MCF-7 and T47D) BC cell lines demonstrated a significant increase in GV formation after stimulation with E2 which was reversed by tamoxifen. ERα-negative (MDA-MB-231 and MDA-MB-468) BC cell lines produced GVs independently of E2 and tamoxifen. These results indicate the existence of both intracellular and extracellular vesicles with considerably larger dimensions than generally recognised with BC cells and suggest that the GVs are regulated by E2 via ERα in ERα-positive BC but by E2-independent mechanisms in ER-ve BC.
Breast cancer; vesicle; estrogen; trafficking; exocytosis
The European Network for Breast Development and Cancer (ENBDC) Workshop on ‘Methods in Mammary Gland Development and Cancer’ has grown into the essential, international technical discussion forum for scientists with interests in the normal and neoplastic breast. The fifth ENBDC meeting was held in Weggis, Switzerland in April, 2013, and focussed on emerging, state-of-the-art techniques for the study of non-coding RNA, lineage tracing, tumor heterogeneity, metastasis and metabolism.