Copy number aberrations from Affymetrix SNP 6.0 genotyping data-how accurate are commonly used prediction approaches?

Copy number aberrations (CNAs) are known to strongly affect oncogenes and tumour suppressor genes. Given the critical role CNAs play in cancer research, it is essential to accurately identify CNAs from tumour genomes. One particular challenge in finding CNAs is the effect of confounding variables. To address this issue, we assessed how commonly used CNA identification algorithms perform on SNP 6.0 genotyping data in the presence of confounding variables. We simulated realistic synthetic data with varying levels of three confounding variables-the tumour purity, the length of a copy number region and the CNA burden (the percentage of CNAs present in a profiled genome)-and evaluated the performance of OncoSNP, ASCAT, GenoCNA, GISTIC and CGHcall. Furthermore, we implemented and assessed CGHcall*, an adjusted version of CGHcall accounting for high CNA burden. Our analysis on synthetic data indicates that tumour purity and the CNA burden strongly influence the performance of all the algorithms. No algorithm can correctly find lost and gained genomic regions across all tumour purities. The length of CNA regions influenced the performance of ASCAT, CGHcall and GISTIC. OncoSNP, GenoCNA and CGHcall* showed little sensitivity. Overall, CGHcall* and OncoSNP showed reasonable performance, particularly in samples with high tumour purity. Our analysis on the HapMap data revealed a good overlap between CGHcall, CGHcall* and GenoCNA results and experimentally validated data. Our exploratory analysis on the TCGA HNSCC data revealed plausible results of CGHcall, CGHcall* and GISTIC in consensus HNSCC CNA regions. Code is available at https://github.com/adspit/PASCAL.

Altered relaxation times in MRI indicate bronchopulmonary dysplasia.

We developed a MRI protocol using transverse (T2) and longitudinal (T1) mapping sequences to characterise lung structural changes in preterm infants with bronchopulmonary dysplasia (BPD). We prospectively enrolled 61 infants to perform 3-Tesla MRI of the lung in quiet sleep. Statistical analysis was performed using logistic Group Lasso regression and logistic regression. Increased lung T2 relaxation time and decreased lung T1 relaxation time indicated BPD yielding an area under the curve (AUC) of 0.80. Results were confirmed in an independent study cohort (AUC 0.75) and mirrored by lung function testing, indicating the high potential for MRI in future BPD diagnostics. TRIAL REGISTRATION: DRKS00004600.

GATA2/3-TFAP2A/C transcription factor network couples human pluripotent stem cell differentiation to trophectoderm with repression of pluripotency.

To elucidate the molecular basis of BMP4-induced differentiation of human pluripotent stem cells (PSCs) toward progeny with trophectoderm characteristics, we produced transcriptome, epigenome H3K4me3, H3K27me3, and CpG methylation maps of trophoblast progenitors, purified using the surface marker APA. We combined them with the temporally resolved transcriptome of the preprogenitor phase and of single APA+ cells. This revealed a circuit of bivalent TFAP2A, TFAP2C, GATA2, and GATA3 transcription factors, coined collectively the "trophectoderm four" (TEtra), which are also present in human trophectoderm in vivo. At the onset of differentiation, the TEtra factors occupy multiple sites in epigenetically inactive placental genes and in OCT4 Functional manipulation of GATA3 and TFAP2A indicated that they directly couple trophoblast-specific gene induction with suppression of pluripotency. In accordance, knocking down GATA3 in primate embryos resulted in a failure to form trophectoderm. The discovery of the TEtra circuit indicates how trophectoderm commitment is regulated in human embryogenesis.

Quantification of regenerative potential in primary human mammary epithelial cells.

We present an organoid regeneration assay in which freshly isolated human mammary epithelial cells are cultured in adherent or floating collagen gels, corresponding to a rigid or compliant matrix environment. In both conditions, luminal progenitors form spheres, whereas basal cells generate branched ductal structures. In compliant but not rigid collagen gels, branching ducts form alveoli at their tips, express basal and luminal markers at correct positions, and display contractility, which is required for alveologenesis. Thereby, branched structures generated in compliant collagen gels resemble terminal ductal-lobular units (TDLUs), the functional units of the mammary gland. Using the membrane metallo-endopeptidase CD10 as a surface marker enriches for TDLU formation and reveals the presence of stromal cells within the CD49f(hi)/EpCAM(-) population. In summary, we describe a defined in vitro assay system to quantify cells with regenerative potential and systematically investigate their interaction with the physical environment at distinct steps of morphogenesis.

RAMONA: a Web application for gene set analysis on multilevel omics data.

SUMMARY: Decreasing costs of modern high-throughput experiments allow for the simultaneous analysis of altered gene activity on various molecular levels. However, these multi-omics approaches lead to a large amount of data, which is hard to interpret for a non-bioinformatician. Here, we present the remotely accessible multilevel ontology analysis (RAMONA). It offers an easy-to-use interface for the simultaneous gene set analysis of combined omics datasets and is an extension of the previously introduced MONA approach. RAMONA is based on a Bayesian enrichment method for the inference of overrepresented biological processes among given gene sets. Overrepresentation is quantified by interpretable term probabilities. It is able to handle data from various molecular levels, while in parallel coping with redundancies arising from gene set overlaps and related multiple testing problems. The comprehensive output of RAMONA is easy to interpret and thus allows for functional insight into the affected biological processes. With RAMONA, we provide an efficient implementation of the Bayesian inference problem such that ontologies consisting of thousands of terms can be processed in the order of seconds. AVAILABILITY AND IMPLEMENTATION: RAMONA is implemented as ASP.NET Web application and publicly available at http://icb.helmholtz-muenchen.de/ramona.

A modular framework for gene set analysis integrating multilevel omics data.

Modern high-throughput methods allow the investigation of biological functions across multiple 'omics' levels. Levels include mRNA and protein expression profiling as well as additional knowledge on, for example, DNA methylation and microRNA regulation. The reason for this interest in multi-omics is that actual cellular responses to different conditions are best explained mechanistically when taking all omics levels into account. To map gene products to their biological functions, public ontologies like Gene Ontology are commonly used. Many methods have been developed to identify terms in an ontology, overrepresented within a set of genes. However, these methods are not able to appropriately deal with any combination of several data types. Here, we propose a new method to analyse integrated data across multiple omics-levels to simultaneously assess their biological meaning. We developed a model-based Bayesian method for inferring interpretable term probabilities in a modular framework. Our Multi-level ONtology Analysis (MONA) algorithm performed significantly better than conventional analyses of individual levels and yields best results even for sophisticated models including mRNA fine-tuning by microRNAs. The MONA framework is flexible enough to allow for different underlying regulatory motifs or ontologies. It is ready-to-use for applied researchers and is available as a standalone application from http://icb.helmholtz-muenchen.de/mona.

MicroRNA-Target Network Inference and Local Network Enrichment Analysis Identify Two microRNA Clusters with Distinct Functions in Head and Neck Squamous Cell Carcinoma.

MicroRNAs represent ~22 nt long endogenous small RNA molecules that have been experimentally shown to regulate gene expression post-transcriptionally. One main interest in miRNA research is the investigation of their functional roles, which can typically be accomplished by identification of mi-/mRNA interactions and functional annotation of target gene sets. We here present a novel method "miRlastic", which infers miRNA-target interactions using transcriptomic data as well as prior knowledge and performs functional annotation of target genes by exploiting the local structure of the inferred network. For the network inference, we applied linear regression modeling with elastic net regularization on matched microRNA and messenger RNA expression profiling data to perform feature selection on prior knowledge from sequence-based target prediction resources. The novelty of miRlastic inference originates in predicting data-driven intra-transcriptome regulatory relationships through feature selection. With synthetic data, we showed that miRlastic outperformed commonly used methods and was suitable even for low sample sizes. To gain insight into the functional role of miRNAs and to determine joint functional properties of miRNA clusters, we introduced a local enrichment analysis procedure. The principle of this procedure lies in identifying regions of high functional similarity by evaluating the shortest paths between genes in the network. We can finally assign functional roles to the miRNAs by taking their regulatory relationships into account. We thoroughly evaluated miRlastic on a cohort of head and neck cancer (HNSCC) patients provided by The Cancer Genome Atlas. We inferred an mi-/mRNA regulatory network for human papilloma virus (HPV)-associated miRNAs in HNSCC. The resulting network best enriched for experimentally validated miRNA-target interaction, when compared to common methods. Finally, the local enrichment step identified two functional clusters of miRNAs that were predicted to mediate HPV-associated dysregulation in HNSCC. Our novel approach was able to characterize distinct pathway regulations from matched miRNA and mRNA data. An R package of miRlastic was made available through: http://icb.helmholtz-muenchen.de/mirlastic.

Comparison of Protein-like Model Particles Fabricated by Micro 3D Printing to Established Standard Particles.

Innovative analytical instruments and development of new methods has provided a better understanding of protein particle formation in biopharmaceuticals but have also challenged the ability to obtain reproducible and reliable measurements. The need for protein-like particle standards mimicking the irregular shape, translucent nature and near-to-neutral buoyancy of protein particles remained one of the hot topics in the field of particle detection and characterization in biopharmaceutical formulations. An innovative protein-like particle model has been developed using two photo polymerization (2PP) printing allowing to fabricate irregularly shaped particles with similar properties as protein particles at precise size of 50 µm and 150 µm, representative of subvisible particles and visible particles, respectively. A study was conducted to compare the morphological, physical, and optical properties of artificially generated protein particles, polystyrene spheres, ETFE, and SU-8 particle standards, along with newly developed protein-like model particles manufactured using 2PP printing. Our results suggest that 2PP printing can be used to produce protein-like particle standards that might facilitate harmonization and standardization of subvisible and visible protein particle characterization across laboratories and organizations.

Visualizing Synaptic Multi-Protein Patterns of Neuronal Tissue With DNA-Assisted Single-Molecule Localization Microscopy.

The development of super-resolution microscopy (SRM) has widened our understanding of biomolecular structure and function in biological materials. Imaging multiple targets within a single area would elucidate their spatial localization relative to the cell matrix and neighboring biomolecules, revealing multi-protein macromolecular structures and their functional co-dependencies. SRM methods are, however, limited to the number of suitable fluorophores that can be imaged during a single acquisition as well as the loss of antigens during antibody washing and restaining for organic dye multiplexing. We report the visualization of multiple protein targets within the pre- and postsynapse in 350-400 nm thick neuronal tissue sections using DNA-assisted single-molecule localization microscopy (SMLM). In a single labeling step, antibodies conjugated with short DNA oligonucleotides visualized multiple targets by sequential exchange of fluorophore-labeled complementary oligonucleotides present in the imaging buffer. This approach avoids potential effects on structural integrity when using multiple rounds of immunolabeling and eliminates chromatic aberration, because all targets are imaged using a single excitation laser wavelength. This method proved robust for multi-target imaging in semi-thin tissue sections with a lateral resolution better than 25 nm, paving the way toward structural cell biology with single-molecule SRM.

Non-canonical Wnt/PCP signalling regulates intestinal stem cell lineage priming towards enteroendocrine and Paneth cell fates.

A detailed understanding of intestinal stem cell (ISC) self-renewal and differentiation is required to treat chronic intestinal diseases. However, the different models of ISC lineage hierarchy1-6 and segregation7-12 are subject to debate. Here, we have discovered non-canonical Wnt/planar cell polarity (PCP)-activated ISCs that are primed towards the enteroendocrine or Paneth cell lineage. Strikingly, integration of time-resolved lineage labelling with single-cell gene expression analysis revealed that both lineages are directly recruited from ISCs via unipotent transition states, challenging the existence of formerly predicted bi- or multipotent secretory progenitors7-12. Transitory cells that mature into Paneth cells are quiescent and express both stem cell and secretory lineage genes, indicating that these cells are the previously described Lgr5+ label-retaining cells7. Finally, Wnt/PCP-activated Lgr5+ ISCs are molecularly indistinguishable from Wnt/ß-catenin-activated Lgr5+ ISCs, suggesting that lineage priming and cell-cycle exit is triggered at the post-transcriptional level by polarity cues and a switch from canonical to non-canonical Wnt/PCP signalling. Taken together, we redefine the mechanisms underlying ISC lineage hierarchy and identify the Wnt/PCP pathway as a new niche signal preceding lateral inhibition in ISC lineage priming and segregation.

Automated highly multiplexed super-resolution imaging of protein nano-architecture in cells and tissues.

Understanding the nano-architecture of protein machines in diverse subcellular compartments remains a challenge despite rapid progress in super-resolution microscopy. While single-molecule localization microscopy techniques allow the visualization and identification of cellular structures with near-molecular resolution, multiplex-labeling of tens of target proteins within the same sample has not yet been achieved routinely. However, single sample multiplexing is essential to detect patterns that threaten to get lost in multi-sample averaging. Here, we report maS3TORM (multiplexed automated serial staining stochastic optical reconstruction microscopy), a microscopy approach capable of fully automated 3D direct STORM (dSTORM) imaging and solution exchange employing a re-staining protocol to achieve highly multiplexed protein localization within individual biological samples. We demonstrate 3D super-resolution images of 15 targets in single cultured cells and 16 targets in individual neuronal tissue samples with <10 nm localization precision, allowing us to define distinct nano-architectural features of protein distribution within the presynaptic nerve terminal.

BART-Seq: cost-effective massively parallelized targeted sequencing for genomics, transcriptomics, and single-cell analysis.

We describe a highly sensitive, quantitative, and inexpensive technique for targeted sequencing of transcript cohorts or genomic regions from thousands of bulk samples or single cells in parallel. Multiplexing is based on a simple method that produces extensive matrices of diverse DNA barcodes attached to invariant primer sets, which are all pre-selected and optimized in silico. By applying the matrices in a novel workflow named Barcode Assembly foR Targeted Sequencing (BART-Seq), we analyze developmental states of thousands of single human pluripotent stem cells, either in different maintenance media or upon Wnt/ß-catenin pathway activation, which identifies the mechanisms of differentiation induction. Moreover, we apply BART-Seq to the genetic screening of breast cancer patients and identify BRCA mutations with very high precision. The processing of thousands of samples and dynamic range measurements that outperform global transcriptomics techniques makes BART-Seq first targeted sequencing technique suitable for numerous research applications.

Maternal whole blood cell miRNA-340 is elevated in gestational diabetes and inversely regulated by glucose and insulin.

The number of pregnancies complicated by gestational diabetes (GDM) is increasing worldwide. To identify novel characteristics of GDM, we studied miRNA profiles of maternal and fetal whole blood cells (WBCs) from GDM and normal glucose tolerant (NGT) pregnant women matched for body mass index and maternal age. After adjustment for maternal weight gain and pregnancy week, we identified 29 mature micro-RNAs (miRNAs) up-regulated in GDM, one of which, i.e., miRNA-340, was validated by qPCR. mRNA and protein expression of PAIP1, a miRNA-340 target gene, was found down-regulated in GDM women, accordingly. In lymphocytes derived from the mothers' blood and treated in vitro, insulin increased and glucose reduced miRNA-340 expression. In fetal cord blood samples, no associations of miRNA-340 with maternal GDM were observed. Our results provide evidence for insulin-induced epigenetic, i.e., miRNA-dependent, programming of maternal WBCs in GDM.

Epigenetically Regulated Chromosome 14q32 miRNA Cluster Induces Metastasis and Predicts Poor Prognosis in Lung Adenocarcinoma Patients.

Most lung cancer deaths are related to metastases, which indicates the necessity of detecting and inhibiting tumor cell dissemination. Here, we aimed to identify miRNAs involved in metastasis of lung adenocarcinoma as prognostic biomarkers and therapeutic targets. To that end, lymph node metastasis-associated miRNAs were identified in The Cancer Genome Atlas lung adenocarcinoma patient cohort (sequencing data; n = 449) and subsequently validated by qRT-PCR in an independent clinical cohort (n = 108). Overexpression of miRNAs located on chromosome 14q32 was associated with metastasis in lung adenocarcinoma patients. Importantly, Kaplan-Meier analysis and log-rank test revealed that higher expression levels of individual 14q32 miRNAs (mir-539, mir-323b, and mir-487a) associated with worse disease-free survival of never-smoker patients. Epigenetic analysis including DNA methylation microarray data and bisulfite sequencing validation demonstrated that the induction of 14q32 cluster correlated with genomic hypomethylation of the 14q32 locus. CRISPR activation technology, applied for the first time to functionally study the increase of clustered miRNA levels in a coordinated manner, showed that simultaneous overexpression of 14q32 miRNAs promoted tumor cell migratory and invasive properties. Analysis of individual miRNAs by mimic transfection further illustrated that miR-323b-3p, miR-487a-3p, and miR-539-5p significantly contributed to the invasive phenotype through the indirect regulation of different target genes. In conclusion, overexpression of 14q32 miRNAs, associated with the respective genomic hypomethylation, promotes metastasis and correlates with poor patient prognosis in lung adenocarcinoma.Implications: This study points to chromosome 14q32 miRNAs as promising targets to inhibit tumor cell dissemination and to predict patient prognosis in lung adenocarcinoma. Mol Cancer Res; 16(3); 390-402. ©2018 AACR.

Inhibition of fat cell differentiation in 3T3-L1 pre-adipocytes by all-trans retinoic acid: Integrative analysis of transcriptomic and phenotypic data.

The process of adipogenesis is controlled in a highly orchestrated manner, including transcriptional and post-transcriptional events. In developing 3T3-L1 pre-adipocytes, this program can be interrupted by all-trans retinoic acid (ATRA). To examine this inhibiting impact by ATRA, we generated large-scale transcriptomic data on the microRNA and mRNA level. Non-coding RNAs such as microRNAs represent a field in RNA turnover, which is very important for understanding the regulation of mRNA gene expression. High throughput mRNA and microRNA expression profiling was performed using mRNA hybridisation microarray technology and multiplexed expression assay for microRNA quantification. After quantitative measurements we merged expression data sets, integrated the results and analysed the molecular regulation of in vitro adipogenesis. For this purpose, we applied local enrichment analysis on the integrative microRNA-mRNA network determined by a linear regression approach. This approach includes the target predictions of TargetScan Mouse 5.2 and 23 pre-selected, significantly regulated microRNAs as well as Affymetrix microarray mRNA data. We found that the cellular lipid metabolism is negatively affected by ATRA. Furthermore, we were able to show that microRNA 27a and/or microRNA 96 are important regulators of gap junction signalling, the rearrangement of the actin cytoskeleton as well as the citric acid cycle, which represent the most affected pathways with regard to inhibitory effects of ATRA in 3T3-L1 preadipocytes. In conclusion, the experimental workflow and the integrative microRNA-mRNA data analysis shown in this study represent a possibility for illustrating interactions in highly orchestrated biological processes. Further the applied global microRNA-mRNA interaction network may also be used for the pre-selection of potential new biomarkers with regard to obesity or for the identification of new pharmaceutical targets.

Calcium-regulatory proteins as modulators of chemotherapy in human neuroblastoma.

Neuroblastoma (NB) is a pediatric cancer treated with poly-chemotherapy including platinum complexes (e.g. cisplatin (CDDP), carboplatin), DNA alkylating agents, and topoisomerase I inhibitors (e.g. topotecan (TOPO)). Despite aggressive treatment, NB may become resistant to chemotherapy. We investigated whether CDDP and TOPO treatment of NB cells interacts with the expression and function of proteins involved in regulating calcium signaling. Human neuroblastoma cell lines SH-SY5Y, IMR-32 and NLF were used to investigate the effects of CDDP and TOPO on cell viability, apoptosis, calcium homeostasis, and expression of selected proteins regulating intracellular calcium concentration ([Ca2+]i). In addition, the impact of pharmacological inhibition of [Ca2+]i-regulating proteins on neuroblastoma cell survival was studied. Treatment of neuroblastoma cells with increasing concentrations of CDDP (0.1-10 µM) or TOPO (0.1 nM-1 µM) induced cytotoxicity and increased apoptosis in a concentration- and time-dependent manner. Both drugs increased [Ca2+]i over time. Treatment with CDDP or TOPO also modified mRNA expression of selected genes encoding [Ca2+]i-regulating proteins. Differentially regulated genes included S100A6, ITPR1, ITPR3, RYR1 and RYR3. With FACS and confocal laser scanning microscopy experiments we validated their differential expression at the protein level. Importantly, treatment of neuroblastoma cells with pharmacological modulators of [Ca2+]i-regulating proteins in combination with CDDP or TOPO increased cytotoxicity. Thus, our results confirm an important role of calcium signaling in the response of neuroblastoma cells to chemotherapy and suggest [Ca2+]i modulation as a promising strategy for adjunctive treatment.

Epigenetic germline inheritance of diet-induced obesity and insulin resistance.

There is considerable controversy regarding epigenetic inheritance in mammalian gametes. Using in vitro fertilization to ensure exclusive inheritance via the gametes, we show that a parental high-fat diet renders offspring more susceptible to developing obesity and diabetes in a sex- and parent of origin-specific mode. The epigenetic inheritance of acquired metabolic disorders may contribute to the current obesity and diabetes pandemic.

The global gene expression profile of the secondary transition during pancreatic development.

Pancreas organogenesis is a highly dynamic process where neighboring tissue interactions lead to dynamic changes in gene regulatory networks that orchestrate endocrine, exocrine, and ductal lineage formation. To understand the spatio-temporal regulatory logic we have used the Forkhead transcription factor Foxa2-Venus fusion (FVF) knock-in reporter mouse to separate the FVF(+) pancreatic epithelium from the FVF(−) surrounding tissue (mesenchyme, neurons, blood, and blood vessels) to perform a genome-wide mRNA expression profiling at embryonic days (E) 12.5-15.5. Annotating genes and molecular processes suggest that FVF marks endoderm-derived multipotent epithelial progenitors at several lineage restriction steps, when the bulk of endocrine, exocrine and ductal cells are formed during the secondary transition. In the pancreatic epithelial compartment, we identified most known endocrine and exocrine lineage determining factors and diabetes-associated genes, but also unknown genes with spatio-temporal regulated pancreatic expression. In the non-endoderm-derived compartment, we identified many well-described regulatory genes that are not yet functionally annotated in pancreas development, emphasizing that neighboring tissue interactions are still ill defined. Pancreatic expression of over 635 genes was analyzed with them RNA in situ hybridization Genepaint public database. This validated the quality of the profiling data set and identified hundreds of genes with spatially restricted expression patterns in the pancreas. Some of these genes are also targeted by pancreatic transcription factors and show active chromatin marks in human islets of Langerhans. Thus, with the highest spatio-temporal resolution of a global gene expression profile during the secondary transition, our study enables to shed light on neighboring tissue interactions, developmental timing and diabetes gene regulation.