Probabilistic pathway-based multimodal factor analysis.

MOTIVATION: Multimodal profiling strategies promise to produce more informative insights into biomedical cohorts via the integration of the information each modality contributes. To perform this integration, however, the development of novel analytical strategies is needed. Multimodal profiling strategies often come at the expense of lower sample numbers, which can challenge methods to uncover shared signals across a cohort. Thus, factor analysis approaches are commonly used for the analysis of high-dimensional data in molecular biology, however, they typically do not yield representations that are directly interpretable, whereas many research questions often center around the analysis of pathways associated with specific observations. RESULTS: We develop PathFA, a novel approach for multimodal factor analysis over the space of pathways. PathFA produces integrative and interpretable views across multimodal profiling technologies, which allow for the derivation of concrete hypotheses. PathFA combines a pathway-learning approach with integrative multimodal capability under a Bayesian procedure that is efficient, hyper-parameter free, and able to automatically infer observation noise from the data. We demonstrate strong performance on small sample sizes within our simulation framework and on matched proteomics and transcriptomics profiles from real tumor samples taken from the Swiss Tumor Profiler consortium. On a subcohort of melanoma patients, PathFA recovers pathway activity that has been independently associated with poor outcome. We further demonstrate the ability of this approach to identify pathways associated with the presence of specific cell-types as well as tumor heterogeneity. Our results show that we capture known biology, making it well suited for analyzing multimodal sample cohorts. AVAILABILITY AND IMPLEMENTATION: The tool is implemented in python and available at https://github.com/ratschlab/path-fa.

Elucidation of host-virus surfaceome interactions using spatial proteotyping.

The cellular surfaceome and its residing extracellularly exposed proteins are involved in a multitude of molecular signaling processes across the viral infection cycle. Successful viral propagation, including viral entry, immune evasion, virion release and viral spread rely on dynamic molecular interactions with the surfaceome. Decoding of these viral-host surfaceome interactions using advanced technologies enabled the discovery of fundamental new functional insights into cellular and viral biology. In this review, we highlight recently developed experimental strategies, with a focus on spatial proteotyping technologies, aiding in the rational design of theranostic strategies to combat viral infections.

The Tumor Profiler Study: integrated, multi-omic, functional tumor profiling for clinical decision support.

The application and integration of molecular profiling technologies create novel opportunities for personalized medicine. Here, we introduce the Tumor Profiler Study, an observational trial combining a prospective diagnostic approach to assess the relevance of in-depth tumor profiling to support clinical decision-making with an exploratory approach to improve the biological understanding of the disease.

An adverse outcome pathway-based approach to assess steatotic mixture effects of hepatotoxic pesticides in vitro.

Exposure to complex chemical mixtures requires a tiered strategy for efficient mixture risk assessment. As a part of the EuroMix project we developed an adverse outcome pathway (AOP)-based assay toolbox to investigate the combined effects of the liver steatosis-inducing compounds imazalil, thiacloprid, and clothianidin in human HepaRG hepatocarcinoma cells. Compound-specific relative potency factors were determined using a benchmark dose approach. Equipotent mixtures were tested for nuclear receptor activation, gene and protein expression, and triglyceride accumulation, according to the molecular initiating events and key events proposed in the steatosis AOP. All three compounds affected the activity of nuclear receptors, but not key genes/proteins as proposed. Triglyceride accumulation was observed with three different methods. Mixture effects were in agreement with the assumption of dose additivity for all the combinations and endpoints tested. Compound-specific RPFs remained similar over the different endpoints studied downstream the AOP. Therefore, it might be possible to reduce testing to a smaller battery of key tests. The results demonstrate the suitability of our in vitro assay toolbox, integrated within an AOP framework and combined with the RPF approach, for the analysis of steatotic effects of chemical mixtures. However, mRNA results suggest that the steatosis AOP still needs improvement.

Surfaceome nanoscale organization and extracellular interaction networks.

The reductionist view of 'one target-one drug' has fueled the development of therapeutic agents to treat human disease. However, many compounds that have efficacy in vitro are inactive in complex in vivo systems. It has become clear that a molecular understanding of signaling networks is needed to address disease phenotypes in the human body. Protein signaling networks function at the molecular level through information transfer via protein-protein interactions. Cell surface exposed proteins, termed the surfaceome, are the gatekeepers between the intra- and extracellular signaling networks, translating extracellular cues into intracellular responses and vice versa. As 66% of drugs in the DrugBank target the surfaceome, these proteins are a key source for potential diagnostic and therapeutic agents. In this review article, we will discuss current knowledge about the spatial organization and molecular interactions of the surfaceome and provide a perspective on the technologies available for studying the extracellular surfaceome interaction network.

Adverse Outcome Pathway-Driven Analysis of Liver Steatosis in Vitro: A Case Study with Cyproconazole.

Adverse outcome pathways (AOPs) describe causal relationships between molecular perturbation and adverse cellular effects and are being increasingly adopted for linking in vitro mechanistic toxicology to in vivo data from regulatory toxicity studies. In this work, a case study was performed by developing a bioassay toolbox to assess key events in the recently proposed AOP for chemically induced liver steatosis. The toolbox is comprised of in vitro assays to measure nuclear receptor activation, gene and protein expression, lipid accumulation, mitochondrial respiration, and formation of fatty liver cells. Assay evaluation was performed in human HepaRG hepatocarcinoma cells exposed to the model compound cyproconazole, a fungicide inducing steatosis in rodents. Cyproconazole dose-dependently activated RARα and PXR, two molecular initiating events in the steatosis AOP. Moreover, cyproconazole provoked a disruption of mitochondrial functions and induced triglyceride accumulation and the formation of fatty liver cells as described in the AOP. Gene and protein expression analysis, however, showed expression changes different from those proposed in the AOP, thus suggesting that the current version of the AOP might not fully reflect the complex mechanisms linking nuclear receptor activation and liver steatosis. Our study shows that cyproconazole induces steatosis in human liver cells in vitro and demonstrates the utility of systems-based approaches in the mechanistic assessment of molecular and cellular key events in an AOP. AOP-driven in vitro testing as demonstrated can further improve existing AOPs, provide insight regarding molecular mechanisms of toxicity, and inform predictive risk assessment.

Parity induces differentiation and reduces Wnt/Notch signaling ratio and proliferation potential of basal stem/progenitor cells isolated from mouse mammary epithelium.

INTRODUCTION: Early pregnancy has a strong protective effect against breast cancer in humans and rodents, but the underlying mechanism is unknown. Because breast cancers are thought to arise from specific cell subpopulations of mammary epithelia, we studied the effect of parity on the transcriptome and the differentiation/proliferation potential of specific luminal and basal mammary cells in mice. METHODS: Mammary epithelial cell subpopulations (luminal Sca1-, luminal Sca1+, basal stem/progenitor, and basal myoepithelial cells) were isolated by flow cytometry from parous and age-matched virgin mice and examined by using a combination of unbiased genomics, bioinformatics, in vitro colony formation, and in vivo limiting dilution transplantation assays. Specific findings were further investigated with immunohistochemistry in entire glands of parous and age-matched virgin mice. RESULTS: Transcriptome analysis revealed an upregulation of differentiation genes and a marked decrease in the Wnt/Notch signaling ratio in basal stem/progenitor cells of parous mice. Separate bioinformatics analyses showed reduced activity for the canonical Wnt transcription factor LEF1/TCF7 and increased activity for the Wnt repressor TCF3. This finding was specific for basal stem/progenitor cells and was associated with downregulation of potentially carcinogenic pathways and a reduction in the proliferation potential of this cell subpopulation in vitro and in vivo. As a possible mechanism for decreased Wnt signaling in basal stem/progenitor cells, we found a more than threefold reduction in the expression of the secreted Wnt ligand Wnt4 in total mammary cells from parous mice, which corresponded to a similar decrease in the proportion of Wnt4-secreting and estrogen/progesterone receptor-positive cells. Because recombinant Wnt4 rescued the proliferation defect of basal stem/progenitor cells in vitro, reduced Wnt4 secretion appears to be causally related to parity-induced alterations of basal stem/progenitor cell properties in mice. CONCLUSIONS: By revealing that parity induces differentiation and downregulates the Wnt/Notch signaling ratio and the in vitro and in vivo proliferation potential of basal stem/progenitor cells in mice, our study sheds light on the long-term consequences of an early pregnancy. Furthermore, it opens the door to future studies assessing whether inhibitors of the Wnt pathway may be used to mimic the parity-induced protective effect against breast cancer.

Protein tyrosine phosphatase 1B restrains mammary alveologenesis and secretory differentiation.

Tyrosine phosphorylation plays a fundamental role in mammary gland development. However, the role of specific tyrosine phosphatases in controlling mammary cell fate remains ill defined. We have identified protein tyrosine phosphatase 1B (PTP1B) as an essential regulator of alveologenesis and lactogenesis. PTP1B depletion increased the number of luminal mammary progenitors in nulliparous mice, leading to enhanced alveoli formation upon pregnancy. Mechanistically, Ptp1b deletion enhanced the expression of progesterone receptor and phosphorylation of Stat5, two key regulators of alveologenesis. Furthermore, glands from Ptp1b knockout mice exhibited increased expression of milk proteins during pregnancy due to enhanced Stat5 activation. These findings reveal that PTP1B constrains the number of mammary progenitors and thus prevents inappropriate onset of alveologenesis in early pregnancy. Moreover, PTP1B restrains the expression of milk proteins during pregnancy and thus prevents premature lactogenesis. Our work has implications for breast tumorigenesis because Ptp1b deletion has been shown to prevent or delay the onset of mammary tumors.