Recurrent heart failure hospitalizations increase the risk of mortality in heart failure patients with atrial fibrillation and type 2 diabetes mellitus in the United Kingdom: a retrospective analysis of Clinical Practice Research Datalink database.

BACKGROUND: Heart failure (HF) is a global illness and is a leading cause of hospitalizations. Recurrent HF hospitalization (HFH) is associated with increased risk of cardiovascular (CV) and all-cause mortality, thereby burdening the health system. Type 2 diabetes mellitus (T2DM) and atrial fibrillation (AF) are two important comorbidities in patients living with HF. This study aims to assess the association between recurrent HFHs with CV and all-cause mortality in patients living with HF and having AF and/or T2DM. METHODS: This study was conducted using primary care data from the Clinical Practice Research Datalink database with linkage to hospital data and mortality data. Adults living with HF and with at least 1 HFH were identified from January 2010 to December 2014. Patients were grouped based on the number of recurrent HFHs. During follow-up, all-cause mortality or CV mortality for the HF population with AF and T2DM was recorded. RESULTS: Overall, 32.9% of 2344 T2DM patients and 28.2% of 4585 AF patients had at least 1 recurrent HFH. The patients were relatively elderly and were predominantly male. The mean number of all-cause hospitalizations in HF patients having T2DM and AF, with ≥ 1 recurrent HFH were significantly higher than patients without recurrent HFH. The annualized mortality rates in CV mortality as the primary cause and for all-cause mortality and increased with recurrent HFHs, in T2DM and AF patients. The risk of CV mortality as primary cause and all cause morality were 5.39 and 3.19 times higher in T2DM patients with 3 recurrent HFHs versus no recurrent HFH. Similarly, the risk of CV mortality as primary cause and all cause morality was 5.98 and 4.3 times higher in AF patients with 3 recurrent HFHs versus those with no recurrent HFH. CONCLUSIONS: Recurrent HFHs are strongly associated with CV mortality and all-cause mortality in HF patients with TD2M or AF. The hospitalization rate highlights the need for treatment and disease management, which will improve the course of the disease and help patients stay out of hospital.

Recurrent heart failure hospitalizations are associated with increased cardiovascular mortality in patients with heart failure in Clinical Practice Research Datalink.

AIMS: Heart failure (HF) is a leading cause of hospitalization and is associated with high morbidity and mortality post-diagnosis. Here, we examined the impact of recurrent HF hospitalization (HFH) on cardiovascular (CV) and all-cause mortality among HF patients. METHODS AND RESULTS: Adult HF patients identified in the Clinical Practice Research Datalink with a first (index) hospitalization due to HF recorded in the Hospital Episode Statistics data set from January 2010 to December 2014 were included. Patients were followed up until death or end of study (December 2017). CV mortality as primary and as any reported cause and all-cause mortality were evaluated. An extended Cox regression model was used for reporting adjusted relative CV mortality rates for time-dependent recurrent HFHs. Overall, 8603 HF patients with an index hospitalization were included, providing 15 964 patient-years of follow-up. Patients were relatively old (median age: 80 years) and were mostly male (54.6%), with main co-morbidities being hypertension and atrial fibrillation. Recurrent HFHs occurred one, two, three, and more than four times in 1561 (18.2%), 518 (6.02%), 206 (2.4%), and 153 (1.8%) patients, respectively. The median time to mortality was 215 (38-664) days for 50.8% of patients who died for any cause during the study period and 139 (27-531) days for 31.3% who died with CV reasons as primary cause. Compared with those of patients without recurrent HFHs, the adjusted hazard ratios (95% CI) for CV mortality as primary cause were 2.65 (2.35-2.99), 3.69 (3.06-4.43), 5.82 (4.48-7.58), and 5.95 (4.40-8.05) for those with one, two, three, and more than four recurrent HFHs. CONCLUSIONS: There is a strong association between recurrent HFH and CV mortality, with the risk increasing progressively with each recurrent HFH.

Transcriptome Characterization of Matched Primary Breast and Brain Metastatic Tumors to Detect Novel Actionable Targets.

BACKGROUND: Breast cancer brain metastases (BrMs) are defined by complex adaptations to both adjuvant treatment regimens and the brain microenvironment. Consequences of these alterations remain poorly understood, as does their potential for clinical targeting. We utilized genome-wide molecular profiling to identify therapeutic targets acquired in metastatic disease. METHODS: Gene expression profiling of 21 patient-matched primary breast tumors and their associated brain metastases was performed by TrueSeq RNA-sequencing to determine clinically actionable BrM target genes. Identified targets were functionally validated using small molecule inhibitors in a cohort of resected BrM ex vivo explants (n = 4) and in a patient-derived xenograft (PDX) model of BrM. All statistical tests were two-sided. RESULTS: Considerable shifts in breast cancer cell-specific gene expression profiles were observed (1314 genes upregulated in BrM; 1702 genes downregulated in BrM; DESeq; fold change > 1.5, Padj < .05). Subsequent bioinformatic analysis for readily druggable targets revealed recurrent gains in RET expression and human epidermal growth factor receptor 2 (HER2) signaling. Small molecule inhibition of RET and HER2 in ex vivo patient BrM models (n = 4) resulted in statistically significantly reduced proliferation (P < .001 in four of four models). Furthermore, RET and HER2 inhibition in a PDX model of BrM led to a statistically significant antitumor response vs control (n = 4, % tumor growth inhibition [mean difference; SD], anti-RET = 86.3% [1176; 258.3], P < .001; anti-HER2 = 91.2% [1114; 257.9], P < .01). CONCLUSIONS: RNA-seq profiling of longitudinally collected specimens uncovered recurrent gene expression acquisitions in metastatic tumors, distinct from matched primary tumors. Critically, we identify aberrations in key oncogenic pathways and provide functional evidence for their suitability as therapeutic targets. Altogether, this study establishes recurrent, acquired vulnerabilities in BrM that warrant immediate clinical investigation and suggests paired specimen expression profiling as a compelling and underutilized strategy to identify targetable dependencies in advanced cancers.

Epigenome-wide SRC-1-Mediated Gene Silencing Represses Cellular Differentiation in Advanced Breast Cancer.

Purpose: Despite the clinical utility of endocrine therapies for estrogen receptor-positive (ER) breast cancer, up to 40% of patients eventually develop resistance, leading to disease progression. The molecular determinants that drive this adaptation to treatment remain poorly understood. Methylome aberrations drive cancer growth yet the functional role and mechanism of these epimutations in drug resistance are poorly elucidated.Experimental Design: Genome-wide multi-omics sequencing approach identified a differentially methylated hub of prodifferentiation genes in endocrine resistant breast cancer patients and cell models. Clinical relevance of the functionally validated methyl-targets was assessed in a cohort of endocrine-treated human breast cancers and patient-derived ex vivo metastatic tumors.Results: Enhanced global hypermethylation was observed in endocrine treatment resistant cells and patient metastasis relative to sensitive parent cells and matched primary breast tumor, respectively. Using paired methylation and transcriptional profiles, we found that SRC-1-dependent alterations in endocrine resistance lead to aberrant hypermethylation that resulted in reduced expression of a set of differentiation genes. Analysis of ER-positive endocrine-treated human breast tumors (n = 669) demonstrated that low expression of this prodifferentiation gene set significantly associated with poor clinical outcome (P = 0.00009). We demonstrate that the reactivation of these genes in vitro and ex vivo reverses the aggressive phenotype.Conclusions: Our work demonstrates that SRC-1-dependent epigenetic remodeling is a 'high level' regulator of the poorly differentiated state in ER-positive breast cancer. Collectively these data revealed an epigenetic reprograming pathway, whereby concerted differential DNA methylation is potentiated by SRC-1 in the endocrine resistant setting. Clin Cancer Res; 24(15); 3692-703. ©2018 AACR.

Network analysis of SRC-1 reveals a novel transcription factor hub which regulates endocrine resistant breast cancer.

Steroid receptor coactivator 1 (SRC-1) interacts with nuclear receptors and other transcription factors (TFs) to initiate transcriptional networks and regulate downstream genes which enable the cancer cell to evade therapy and metastasise. Here we took a top-down discovery approach to map out the SRC-1 transcriptional network in endocrine resistant breast cancer. First, rapid immunoprecipitation mass spectrometry of endogenous proteins (RIME) was employed to uncover new SRC-1 TF partners. Next, RNA sequencing (RNAseq) was undertaken to investigate SRC-1 TF target genes. Molecular and patient-derived xenograft studies confirmed STAT1 as a new SRC-1 TF partner, important in the regulation of a cadre of four SRC-1 transcription targets, NFIA, SMAD2, E2F7 and ASCL1. Extended network analysis identified a downstream 79 gene network, the clinical relevance of which was investigated in RNAseq studies from matched primary and local-recurrence tumours from endocrine resistant patients. We propose that SRC-1 can partner with STAT1 independently of the estrogen receptor to initiate a transcriptional cascade and control regulation of key endocrine resistant genes.

Glycolysis and pyrimidine biosynthesis are required for replication of adherent-invasive Escherichia coli in macrophages.

Adherent-invasive Escherichia coli (AIEC) have been implicated in the aetiology of Crohn's disease (CD), a chronic inflammatory bowel condition. It has been proposed that AIEC-infected macrophages produce high levels of pro-inflammatory cytokines thus contributing to the inflammation observed in CD. AIEC can replicate in macrophages and we wanted to determine if bacterial replication was linked to the high level of cytokine production associated with AIEC-infected macrophages. Therefore, we undertook a genetic analysis of the metabolic requirements for AIEC replication in the macrophage and we show that AIEC replication in this niche is dependent on bacterial glycolysis. In addition, our analyses indicate that AIEC have access to a wide range of nutrients in the macrophage, although the levels of purines and pyrimidines do appear to be limiting. Finally, we show that the macrophage response to AIEC infection is indistinguishable from the response to the non-replicating glycolysis mutant (ΔpfkAB) and a non-pathogenic strain of E. coli, MG1655. Therefore, AIEC does not appear to subvert the normal macrophage response to E. coli during infection.

Adaptation to AI Therapy in Breast Cancer Can Induce Dynamic Alterations in ER Activity Resulting in Estrogen-Independent Metastatic Tumors.

PURPOSE: Acquired resistance to aromatase inhibitor (AI) therapy is a major clinical problem in the treatment of breast cancer. The detailed mechanisms of how tumor cells develop this resistance remain unclear. Here, the adapted function of estrogen receptor (ER) to an estrogen-depleted environment following AI treatment is reported. EXPERIMENTAL DESIGN: Global ER chromatin immuno-precipitation (ChIP)-seq analysis of AI-resistant cells identified steroid-independent ER target genes. Matched patient tumor samples, collected before and after AI treatment, were used to assess ER activity. RESULTS: Maintained ER activity was observed in patient tumors following neoadjuvant AI therapy. Genome-wide ER-DNA-binding analysis in AI-resistant cell lines identified a subset of classic ligand-dependent ER target genes that develop steroid independence. The Kaplan-Meier analysis revealed a significant association between tumors, which fail to decrease this steroid-independent ER target gene set in response to neoadjuvant AI therapy, and poor disease-free survival and overall survival (n = 72 matched patient tumor samples, P = 0.00339 and 0.00155, respectively). The adaptive ER response to AI treatment was highlighted by the ER/AIB1 target gene, early growth response 3 (EGR3). Elevated levels of EGR3 were detected in endocrine-resistant local disease recurrent patient tumors in comparison with matched primary tissue. However, evidence from distant metastatic tumors demonstrates that the ER signaling network may undergo further adaptations with disease progression as estrogen-independent ER target gene expression is routinely lost in established metastatic tumors. CONCLUSIONS: Overall, these data provide evidence of a dynamic ER response to endocrine treatment that may provide vital clues for overcoming the clinical issue of therapy resistance. Clin Cancer Res; 22(11); 2765-77. ©2016 AACR.

Transcriptomic Profiling of Sequential Tumors from Breast Cancer Patients Provides a Global View of Metastatic Expression Changes Following Endocrine Therapy.

PURPOSE: Disease recurrence is a common problem in breast cancer and yet the mechanisms enabling tumor cells to evade therapy and colonize distant organs remain unclear. We sought to characterize global expression changes occurring with metastatic disease progression in the endocrine-resistant setting. EXPERIMENTAL DESIGN: Here, for the first time, RNAsequencing has been performed on matched primary, nodal, and liver metastatic tumors from tamoxifen-treated patients following disease progression. Expression of genes commonly elevated in the metastases of sequenced patients was subsequently examined in an extended matched patient cohort with metastatic disease from multiple sites. The impact of tamoxifen treatment on endocrine-resistant tumors in vivo was investigated in a xenograft model. RESULTS: The extent of patient heterogeneity at the gene level was striking. Less than 3% of the genes differentially expressed between sequential tumors were common to all patients. Larger divergence was observed between primary and liver tumors than between primary and nodal tumors, reflecting both the latency to disease progression and the genetic impact of intervening therapy. Furthermore, an endocrine-resistant in vivo mouse model demonstrated that tamoxifen treatment has the potential to drive disease progression and establish distant metastatic disease. Common functional pathways altered during metastatic, endocrine-resistant progression included extracellular matrix receptor interactions and focal adhesions. CONCLUSIONS: This novel global analysis highlights the influence of primary tumor biology in determining the transcriptomic profile of metastatic tumors, as well as the need for adaptations in cell-cell communications to facilitate successful tumor cell colonization of distant host organs.

Downregulation of Umbilical Cord Blood Levels of miR-374a in Neonatal Hypoxic Ischemic Encephalopathy.

OBJECTIVE: To investigate the expression profile of microRNA (miRNA) in umbilical cord blood from infants with hypoxic ischemic encephalopathy (HIE). STUDY DESIGN: Full-term infants with perinatal asphyxia were identified under strict enrollment criteria. Degree of encephalopathy was defined using both continuous multichannel electroencephalogram in the first 24 hours of life and modified Sarnat score. Seventy infants (18 controls, 33 with perinatal asphyxia without HIE, and 19 infants with HIE [further graded as 13 mild, 2 moderate, and 4 severe]) were included in the study. MiRNA expression profiles were determined using a microarray assay and confirmed using quantitative real-time polymerase chain reaction. RESULTS: Seventy miRNAs were differentially expressed between case and control groups. Of these hsa-miR-374a was the most significantly downregulated in infants with HIE vs controls. Validation of hsa-miR-374a expression using quantitative real-time polymerase chain reaction confirmed a significant reduction in expression among infants with HIE compared with those with perinatal asphyxia and healthy controls (mean relative quantification [SD] = 0.52 [0.37] vs 1.10 [1.52] vs 1.76 [1.69], P < .02). CONCLUSIONS: We have shown a significant step-wise downregulation of hsa-miR-374a expression in cord blood of infants with perinatal asphyxia and subsequent HIE.

Global gene repression by the steroid receptor coactivator SRC-1 promotes oncogenesis.

Transcriptional control is the major determinant of cell fate. The steroid receptor coactivator (SRC)-1 enhances the activity of the estrogen receptor in breast cancer cells, where it confers cell survival benefits. Here, we report that a global analysis of SRC-1 target genes suggested that SRC-1 also mediates transcriptional repression in breast cancer cells. Combined SRC-1 and HOXC11 ChIPseq analysis identified the differentiation marker, CD24, and the apoptotic protein, PAWR, as direct SRC-1/HOXC11 suppression targets. Reduced expression of both CD24 and PAWR was associated with disease progression in patients with breast cancer, and their expression was suppressed in metastatic tissues. Investigations in endocrine-resistant breast cancer cell lines and SRC-1(-/-)/PyMT mice confirmed a role for SRC-1 and HOXC11 in downregulation of CD24 and PAWR. Through bioinformatic analysis and liquid chromatography/mass spectrometry, we identified AP1 proteins and Jumonji domain containing 2C (JMD2C/KDM4C), respectively, as members of the SRC-1 interactome responsible for transcriptional repression. Our findings deepen the understanding of how SRC-1 controls transcription in breast cancers.

Identification of a unique hybrid macrophage-polarization state following recovery from lipopolysaccharide tolerance.

LPS tolerance is an essential immune-homeostatic response to repeated exposure to LPS that prevents excessive inflammatory responses. LPS tolerance induces a state of altered responsiveness in macrophages, resulting in repression of proinflammatory gene expression and increased expression of factors that mediate the resolution of inflammation. In this study, we analyzed the transcriptional plasticity of macrophages following LPS tolerance using genome-wide transcriptional profiling. We demonstrate that LPS tolerance is a transient state and that the expression of proinflammatory genes is restored to levels comparable to the acute response to LPS. However, following recovery from LPS tolerance a number of genes remained locked in a tolerizable state, including IL-33, CD86, IL-10, and NFIL3. Furthermore, we identified of a number of genes uniquely induced following recovery from LPS tolerance. Thus, macrophages adopt a unique transcriptional profile following recovery from LPS tolerance and have a distinct expression pattern of regulators of Ag presentation, antiviral responses, and transcription factors. Our data suggest that recovery from LPS tolerance leads to a hybrid macrophage activation state that is proinflammatory and microbicidal in nature but that possesses a regulatory anti-inflammatory profile distinct from that of LPS-tolerant and LPS-activated macrophages.

Global characterization of the SRC-1 transcriptome identifies ADAM22 as an ER-independent mediator of endocrine-resistant breast cancer.

The development of breast cancer resistance to endocrine therapy results from an increase in cellular plasticity that permits the emergence of a hormone-independent tumor. The steroid coactivator protein SRC-1, through interactions with developmental proteins and other nonsteroidal transcription factors, drives this tumor adaptability. In this discovery study, we identified ADAM22, a non-protease member of the ADAM family of disintegrins, as a direct estrogen receptor (ER)-independent target of SRC-1. We confirmed SRC-1 as a regulator of ADAM22 by molecular, cellular, and in vivo studies. ADAM22 functioned in cellular migration and differentiation, and its levels were increased in endocrine resistant-tumors compared with endocrine-sensitive tumors in mouse xenograft models of human breast cancer. Clinically, ADAM22 was found to serve as an independent predictor of poor disease-free survival. Taken together, our findings suggest that SRC-1 switches steroid-responsive tumors to a steroid-resistant state in which the SRC-1 target gene ADAM22 has a critical role, suggesting this molecule as a prognostic and therapeutic drug target that could help improve the treatment of endocrine-resistant breast cancer.

Chemostat-based transcriptional analysis of growth rate change and BCL-2 over-expression in NS0 cells.

We investigated the transcriptional response of NS0 cells undergoing controlled nutrient growth change in continuous chemostat culture using mouse microarrays. A 50% reduction in growth rate resulted in detectable alterations in the expression of 29 genes in NS0 cells. Notably, expression of genes in three major biological processes, namely transcriptional, translational, and protein processing functions, were modified. To further elucidate the advantage of the chemostat environment for establishment of "omic" data sets, an expression profile of the over-expressed gene bcl-2 in NS0 cells was probed. Functional analysis revealed that the underlying altered molecular mechanism was particularly associated with G1 cell cycle progression, protein synthesis, and apoptosis. Importantly, these findings agreed with the physical function of the cells. Despite an increase in survival rate, bcl-2 over-expression resulted in a decrease of specific productivity, glucose consumption, oxygen uptake rate and intracellular protein content, indicating a lower energy generating metabolism. Further, a prolongation of G1 cell cycle phase was evident on lowering the growth rate. Overall, the application of microarray analysis to chemostat-grown cultures offers an excellent combination for the interpretation of transcriptomic profiles to elucidate the molecular mechanisms during nutrient growth change and bcl-2 over-expression.

Altered cytoplasmic-to-nuclear ratio of survivin is a prognostic indicator in breast cancer.

PURPOSE: Survivin (BIRC5) is a promising tumor biomarker. Conflicting data exist on its prognostic effect in breast cancer. These data may at least be partly due to the manual interpretation of immunohistochemical staining, especially as survivin can be located in both the nucleus and cytoplasm. Quantitative determination of survivin expression using image analysis offers the opportunity to develop alternative scoring models for survivin immunohistochemistry. Here, we present such a model. EXPERIMENTAL DESIGN: A breast cancer tissue microarray containing 102 tumors was stained with an anti-survivin antibody. Whole-slide scanning was used to capture high-resolution images. These images were analyzed using automated algorithms to quantify the staining. RESULTS: Increased nuclear, but not cytoplasmic, survivin was associated with a reduced overall survival (OS; P = 0.038) and disease-specific survival (P = 0.0015). A high cytoplasmic-to-nuclear ratio (CNR) of survivin was associated with improved OS (P = 0.005) and disease-specific survival (P = 0.05). Multivariate analysis revealed that the survivin CNR was an independent predictor of OS (hazard ratio, 0.09; 95% confidence interval, 0.01-0.76; P = 0.027). A survivin CNR of >5 correlated positively with estrogen receptor (P = 0.019) and progesterone receptor (P = 0.033) levels, whereas it was negatively associated with Ki-67 expression (P = 0.04), p53 status (P = 0.005), and c-myc amplification (P = 0.016). CONCLUSION: Different prognostic information is supplied by nuclear and cytoplasmic survivin in breast cancer. Nuclear survivin is a poor prognostic marker in breast cancer. Moreover, CNR of survivin, as determined by image analysis, is an independent prognostic factor.

Comparative proteomics profiling of a phospholamban mutant mouse model of dilated cardiomyopathy reveals progressive intracellular stress responses.

Defective mobilization of Ca2+ by cardiomyocytes can lead to cardiac insufficiency, but the causative mechanisms leading to congestive heart failure (HF) remain unclear. In the present study we performed exhaustive global proteomics surveys of cardiac ventricle isolated from a mouse model of cardiomyopathy overexpressing a phospholamban mutant, R9C (PLN-R9C), and exhibiting impaired Ca2+ handling and death at 24 weeks and compared them with normal control littermates. The relative expression patterns of 6190 high confidence proteins were monitored by shotgun tandem mass spectrometry at 8, 16, and 24 weeks of disease progression. Significant differential abundance of 593 proteins was detected. These proteins mapped to select biological pathways such as endoplasmic reticulum stress response, cytoskeletal remodeling, and apoptosis and included known biomarkers of HF (e.g. brain natriuretic peptide/atrial natriuretic factor and angiotensin-converting enzyme) and other indicators of presymptomatic functional impairment. These altered proteomic profiles were concordant with cognate mRNA patterns recorded in parallel using high density mRNA microarrays, and top candidates were validated by RT-PCR and Western blotting. Mapping of our highest ranked proteins against a human diseased explant and to available data sets indicated that many of these proteins could serve as markers of disease. Indeed we showed that several of these proteins are detectable in mouse and human plasma and display differential abundance in the plasma of diseased mice and affected patients. These results offer a systems-wide perspective of the dynamic maladaptions associated with impaired Ca2+ homeostasis that perturb myocyte function and ultimately converge to cause HF.

Influence of acute phytochemical intake on human urinary metabolomic profiles.

BACKGROUND: Diversity in dietary intake contributes to variation in human metabolomic profiles and artifacts from acute dietary intake can affect metabolomics data. OBJECTIVE: We investigated the role of dietary phytochemicals on shaping human urinary metabolomic profiles. DESIGN: First void urine samples were collected from 21 healthy volunteers (12 women, 9 men) following their normal diet (ND), a 2-d low-phytochemical diet (LPD), or a 2-d standard phytochemical diet (SPD). Nutrient intake was assessed during the study. Urine samples were analyzed by using (1)H nuclear magnetic resonance spectroscopy ((1)H NMR) and mass spectrometry (MS), which was followed by multivariate data analysis. RESULTS: Macronutrient intake did not change throughout the study. Partial least-squares-discriminant analysis indicated a clear distinction between the LPD samples and the ND and SPD samples, relating to creatinine and methylhistidine excretion after the LPD and hippurate excretion after the ND and SPD. The predictive power of the LPD versus the ND model was 74 +/- 3% and 82 +/- 6% with the (1)H NMR and MS data sets, respectively. The predictive power of the LPD versus the SPD model was 83 +/- 8% and 69 +/- 4% for the (1)H NMR and MS data sets respectively. A cross platform comparison of both data sets by co-inertia analysis showed a similar distinction between the LPD and SPD. CONCLUSIONS: Acute changes in urinary metabolomic profiles occur after the consumption of dietary phytochemicals. Dietary restrictions in the 24 h before sample collection may reduce diversity in phytochemical intakes and therefore reduce variation and improve data interpretation in metabolomics studies using urine.

A multivariate analysis approach to the integration of proteomic and gene expression data.

In order to understand even the simplest cellular processes, we need to integrate proteomic, gene expression and other biomolecular data. To date, most computational approaches aimed at integrating proteomics and gene expression data use direct gene/protein correlation measures. However, due to post-transcriptional and translational regulations, the correspondence between the expression of a gene and its protein is complicated. We apply a multivariate statistical method, co-inertia analysis (CIA), to visualise gene and proteomic expression data stemming from the same biological samples. Principal components analysis or correspondence analysis can be used for data exploration on single datasets. CIA is then used to explore the relationships between two or more datasets. We further explore the data by projecting gene ontology (GO) information onto these plots to describe the cellular processes in action. We apply these techniques to gene expression and protein abundance data from studies of the human malarial parasite life cycle and the NCI-60 cancer cell lines. In each case, we visualise gene expression, protein abundance and GO classes in the same low dimensional projections and identify GO classes that are likely to be of biological importance.

CENP-F expression is associated with poor prognosis and chromosomal instability in patients with primary breast cancer.

DNA microarrays have the potential to classify tumors according to their transcriptome. Tissue microarrays (TMAs) facilitate the validation of biomarkers by offering a high-throughput approach to sample analysis. We reanalyzed a high profile breast cancer DNA microarray dataset containing 96 tumor samples using a powerful statistical approach, between group analyses. Among the genes we identified was centromere protein-F (CENP-F), a gene associated with poor prognosis. In a published follow-up breast cancer DNA microarray study, comprising 295 tumour samples, we found that CENP-F upregulation was significantly associated with worse overall survival (p<0.001) and reduced metastasis-free survival (p<0.001). To validate and expand upon these findings, we used 2 independent breast cancer patient cohorts represented on TMAs. CENP-F protein expression was evaluated by immunohistochemistry in 91 primary breast cancer samples from cohort I and 289 samples from cohort II. CENP-F correlated with markers of aggressive tumor behavior including ER negativity and high tumor grade. In cohort I, CENP-F was significantly associated with markers of CIN including cyclin E, increased telomerase activity, c-Myc amplification and aneuploidy. In cohort II, CENP-F correlated with VEGFR2, phosphorylated Ets-2 and Ki67, and in multivariate analysis, was an independent predictor of worse breast cancer-specific survival (p=0.036) and overall survival (p=0.040). In conclusion, we identified CENP-F as a biomarker associated with poor outcome in breast cancer and showed several novel associations of biological significance.

Application of DNA microarray technology in determining breast cancer prognosis and therapeutic response.

There are > 1.15 million cases of breast cancer diagnosed worldwide annually, and it is the second leading cause of cancer death in the European Union. The optimum management of patients with breast cancer requires accurate prognostic and predictive factors. At present, only a small number of such factors are used clinically. DNA microarrays have the potential to measure the expression of tens of thousands of genes simultaneously. Recent preliminary findings suggest that DNA microarray-based gene expression profiling can provide powerful and independent prognostic information in patients with newly diagnosed breast cancer. As well as providing prognostic information, emerging results suggest that DNA microarrays can also be used for predicting response or resistance to treatment, especially to neoadjuvant chemotherapy. Prior to clinical application, these preliminary findings must be validated using large-scale prospective studies. This article reviews these advances and also examines the role of DNA microarrays in reducing the number of patients who receive inappropriate chemotherapy. The most recent data supporting the integration of various publicly available data sets is also reviewed in detail.

Evolution of the MAT locus and its Ho endonuclease in yeast species.

The genetics of the mating-type (MAT) locus have been studied extensively in Saccharomyces cerevisiae, but relatively little is known about how this complex system evolved. We compared the organization of MAT and mating-type-like (MTL) loci in nine species spanning the hemiascomycete phylogenetic tree. We inferred that the system evolved in a two-step process in which silent HMR/HML cassettes appeared, followed by acquisition of the Ho endonuclease from a mobile genetic element. Ho-mediated switching between an active MAT locus and silent cassettes exists only in the Saccharomyces sensu stricto group and their closest relatives: Candida glabrata, Kluyveromyces delphensis, and Saccharomyces castellii. We identified C. glabrata MTL1 as the ortholog of the MAT locus of K. delphensis and show that switching between C. glabrata MTL1a and MTL1alpha genotypes occurs in vivo. The more distantly related species Kluyveromyces lactis has silent cassettes but switches mating type without the aid of Ho endonuclease. Very distantly related species such as Candida albicans and Yarrowia lipolytica do not have silent cassettes. In Pichia angusta, a homothallic species, we found MATalpha2, MATalpha1, and MATa1 genes adjacent to each other on the same chromosome. Although some continuity in the chromosomal location of the MAT locus can be traced throughout hemiascomycete evolution and even to Neurospora, the gene content of the locus has changed with the loss of an HMG domain gene (MATa2) from the MATa idiomorph shortly after HO was recruited.