Reperfusion therapy for ST elevation acute myocardial infarction 2010/2011: current status in 37 ESC countries

Aims Primary percutaneous coronary intervention (PPCI) is the preferred reperfusion therapy in ST-elevation myocardial infarction (STEMI). We conducted this study to evaluate the contemporary status on the use and type of reperfusion therapy in patients admitted with STEMI in the European Society of Cardiology (ESC) member countries. Methods and results A cross-sectional descriptive study based on aggregated country-level data on the use of reperfusion therapy in patients admitted with STEMI during 2010 or 2011. Thirty-seven ESC countries were able to provide data from existing national or regional registries. In countries where no such registries exist, data were based on best expert estimates. Data were collected on the use of STEMI reperfusion treatment and mortality, the numbers of cardiologists, and the availability of PPCI facilities in each country. Our survey provides a brief data summary of the degree of variation in reperfusion therapy across Europe. The number of PPCI procedures varied between countries, ranging from 23 to 884 per million inhabitants. Primary percutaneous coronary intervention and thrombolysis were the dominant reperfusion strategy in 33 and 4 countries, respectively. The mean population served by a single PPCI centre with a 24-h service 7 days a week ranged from 31 300 inhabitants per centre to 6 533 000 inhabitants per centre. Twenty-seven of the total 37 countries participated in a former survey from 2007, and major increases in PPCI utilization were observed in 13 of these countries. Conclusion Large variations in reperfusion treatment are still present across Europe. Countries in Eastern and Southern Europe reported that a substantial number of STEMI patients are not receiving any reperfusion therapy. Implementation of the best reperfusion therapy as recommended in the guidelines should be encourage

De novo missense variants in FBXW11 cause diverse developmental phenotypes including brain, eye and digit anomalies

The identification of genetic variants implicated in human developmental disorders has been revolutionized by second-generation sequencing combined with international pooling of cases. Here, we describe seven individuals who have diverse yet overlapping developmental anomalies, and who all have de novo missense FBXW11 variants identified by whole exome or whole genome sequencing and not reported in the gnomAD database. Their phenotypes include striking neurodevelopmental, digital, jaw, and eye anomalies, and in one individual, features resembling Noonan syndrome, a condition caused by dysregulated RAS signaling. FBXW11 encodes an F-box protein, part of the Skp1-cullin-F-box (SCF) ubiquitin ligase complex, involved in ubiquitination and proteasomal degradation and thus fundamental to many protein regulatory processes. FBXW11 targets include b-catenin and GLI transcription factors, key mediators of Wnt and Hh signaling, respectively, critical to digital, neurological, and eye development. Structural analyses indicate affected residues cluster at the surface of the loops of the substrate-binding domain of FBXW11, and the variants are predicted to destabilize the protein and/or its interactions. In situ hybridization studies on human and zebrafish embryonic tissues demonstrate FBXW11 is expressed in the developing eye, brain, mandibular processes, and limb buds or pectoral fins. Knockdown of the zebrafish FBXW11 orthologs fbxw11a and fbxw11b resulted in embryos with smaller, misshapen, and underdeveloped eyes and abnormal jaw and pectoral fin development. Our findings support the role of FBXW11 in multiple developmental processes, including those involving the brain, eye, digits, and jaw

Effects of eight neuropsychiatric copy number variants on human brain structure

Many copy number variants (CNVs) confer risk for the same range of neurodevelopmental symptoms and psychiatric conditions including autism and schizophrenia. Yet, to date neuroimaging studies have typically been carried out one mutation at a time, showing that CNVs have large effects on brain anatomy. Here, we aimed to characterize and quantify the distinct brain morphometry effects and latent dimensions across 8 neuropsychiatric CNVs. We analyzed T1-weighted MRI data from clinically and non-clinically ascertained CNV carriers (deletion/duplication) at the 1q21.1 (n = 39/28), 16p11.2 (n = 87/78), 22q11.2 (n = 75/30), and 15q11.2 (n = 72/76) loci as well as 1296 non-carriers (controls). Case-control contrasts of all examined genomic loci demonstrated effects on brain anatomy, with deletions and duplications showing mirror effects at the global and regional levels. Although CNVs mainly showed distinct brain patterns, principal component analysis (PCA) loaded subsets of CNVs on two latent brain dimensions, which explained 32 and 29% of the variance of the 8 Cohen’s d maps. The cingulate gyrus, insula, supplementary motor cortex, and cerebellum were identified by PCA and multi-view pattern learning as top regions contributing to latent dimension shared across subsets of CNVs. The large proportion of distinct CNV effects on brain morphology may explain the small neuroimaging effect sizes reported in polygenic psychiatric conditions. Nevertheless, latent gene brain morphology dimensions will help subgroup the rapidly expanding landscape of neuropsychiatric variants and dissect the heterogeneity of idiopathic conditions

Microarray-Based RNA Profiling of Breast Cancer: Batch Effect Removal Improves Cross-Platform Consistency

Microarray is a powerful technique used extensively for gene expression analysis. Different technologies are available, but lack of standardization makes it challenging to compare and integrate data. Furthermore, batch-related biases within datasets are common but often not tackled. We have analyzed the same 234 breast cancers on two different microarray platforms. One dataset contained known batch-effects associated with the fabrication procedure used. The aim was to assess the significance of correcting for systematic batch-effects when integrating data from different platforms. We here demonstrate the importance of detecting batch-effects and how tools, such as ComBat, can be used to successfully overcome such systematic variations in order to unmask essential biological signals. Batch adjustment was found to be particularly valuable in the detection of more delicate differences in gene expression. Furthermore, our results show that prober adjustment is essential for integration of gene expression data obtained from multiple sources. We show that high-variance genes are highly reproducibly expressed across platforms making them particularly well suited as biomarkers and for building gene signatures, exemplified by prediction of estrogen-receptor status and molecular subtypes. In conclusion, the study emphasizes the importance of utilizing proper batch adjustment methods when integrating data across different batches and platforms

RNA profiling reveals familial aggregation of molecular subtypes in non-BRCA1/2 breast cancer families

BACKGROUND: In more than 70% of families with a strong history of breast and ovarian cancers, pathogenic mutation in BRCA1 or BRCA2 cannot be identified, even though hereditary factors are expected to be involved. It has been proposed that tumors with similar molecular phenotypes also share similar underlying pathophysiological mechanisms. In the current study, the aim was to investigate if global RNA profiling can be used to identify functional subgroups within breast tumors from families tested negative for BRCA1/2 germline mutations and how these subgroupings relate to different breast cancer patients within the same family. METHODS: In the current study we analyzed a collection of 70 frozen breast tumor biopsies from a total of 58 families by global RNA profiling and promoter methylation analysis. RESULTS: We show that distinct functional subgroupings, similar to the intrinsic molecular breast cancer subtypes, exist among non-BRCA1/2 breast cancers. The distribution of subtypes was markedly different from the distribution found among BRCA1/2 mutation carriers. From 11 breast cancer families, breast tumor biopsies from more than one affected family member were included in the study. Notably, in 8 of these families we found that patients from the same family shared the same tumor subtype, showing a tendency of familial aggregation of tumor subtypes (p-value = 1.7e-3). Using our previously developed BRCA1/2-signatures, we identified 7 non-BRCA1/2 tumors with a BRCA1-like molecular phenotype and provide evidence for epigenetic inactivation of BRCA1 in three of the tumors. In addition, 7 BRCA2-like tumors were found. CONCLUSIONS: Our finding indicates involvement of hereditary factors in non-BRCA1/2 breast cancer families in which family members may carry genetic susceptibility not just to breast cancer but to a particular subtype of breast cancer. This is the first study to provide a biological link between breast cancers from family members of high-risk non-BRCA1/2 families in a systematic manner, suggesting that future genetic analysis may benefit from subgrouping families into molecularly homogeneous subtypes in order to search for new high penetrance susceptibility genes

Comparison of the Metastasis Predictive Potential of mRNA and Long Non-Coding RNA Profiling in Systemically Untreated Breast Cancer

Several gene expression signatures based on mRNAs and a few based on long non-coding RNAs (lncRNAs) have been developed to provide prognostic information beyond clinical evaluation in breast cancer (BC). However, the comparison of such signatures for predicting recurrence is very scarce. Therefore, we compared the prognostic utility of mRNAs and lncRNAs in low-risk BC patients using two different classification strategies. Frozen primary tumor samples from 160 lymph node negative and systemically untreated BC patients were included; 80 developed recurrence—i.e., regional or distant metastasis while 80 remained recurrence-free (mean follow-up of 20.9 years). Patients were pairwise matched for clinicopathological characteristics. Classification based on differential mRNA or lncRNA expression using seven individual machine learning methods and a voting scheme classified patients into risk-subgroups. Classification by the seven methods with a fixed sensitivity of ≥90% resulted in specificities ranging from 16–40% for mRNA and 38–58% for lncRNA, and after voting, specificities of 38% and 60% respectively. Classifier performance based on an alternative classification approach of balanced accuracy optimization also provided higher specificities for lncRNA than mRNA at comparable sensitivities. Thus, our results suggested that classification followed by voting improved prognostic power using lncRNAs compared to mRNAs regardless of classification strategy

Classifications within Molecular Subtypes Enables Identification of BRCA1/BRCA2 Mutation Carriers by RNA Tumor Profiling

Pathogenic germline mutations in BRCA1 or BRCA2 are detected in less than one third of families with a strong history of breast cancer. It is therefore expected that mutations still remain undetected by currently used screening methods. In addition, a growing number of BRCA1/2 sequence variants of unclear pathogen significance are found in the families, constituting an increasing clinical challenge. New methods are therefore needed to improve the detection rate and aid the interpretation of the clinically uncertain variants. In this study we analyzed a series of 33 BRCA1, 22 BRCA2, and 128 sporadic tumors by RNA profiling to investigate the classification potential of RNA profiles to predict BRCA1/2 mutation status. We found that breast tumors from BRCA1 and BRCA2 mutation carriers display characteristic RNA expression patterns, allowing them to be distinguished from sporadic tumors. The majority of BRCA1 tumors were basal-like while BRCA2 tumors were mainly luminal B. Using RNA profiles, we were able to distinguish BRCA1 tumors from sporadic tumors among basal-like tumors with 83% accuracy and BRCA2 from sporadic tumors among luminal B tumors with 89% accuracy. Furthermore, subtype-specific BRCA1/2 gene signatures were successfully validated in two independent data sets with high accuracies. Although additional validation studies are required, indication of BRCA1/2 involvement ("BRCAness") by RNA profiling could potentially be valuable as a tool for distinguishing pathogenic mutations from benign variants, for identification of undetected mutation carriers, and for selecting patients sensitive to new therapeutics such as PARP inhibitors