Lymphatic vessels are essential for immune surveillance, tissue fluid homeostasis and fat absorption. Defects in lymphatic vessel formation or function cause lymphedema. Here we show that the vascular endothelial growth factor C (VEGF-C) is required for the initial steps in lymphatic development. In Vegfc-/- mice, endothelial cells commit to the lymphatic lineage but do not sprout to form lymph vessels. Sprouting was rescued by VEGF-C and VEGF-D but not by VEGF, indicating VEGF receptor 3 specificity. The lack of lymphatic vessels resulted in prenatal death due to fluid accumulation in tissues, and Vegfc+/- mice developed cutaneous lymphatic hypoplasia and lymphedema. Our results indicate that VEGF-C is the paracrine factor essential for lymphangiogenesis, and show that both Vegfc alleles are required for normal lymphatic development.

Modified risk tobacco products (MRTP) are designed to reduce smoking-related health risks. A murine model of chronic obstructive pulmonary disease (COPD) was applied to investigate classical toxicology end points plus systems toxicology (transcriptomics and proteomics). C57BL/6 mice were exposed to conventional cigarette smoke (3R4F), fresh air (sham), or a prototypic MRTP (pMRTP) aerosol for up to 7 months, including a cessation group and a switching-to-pMRTP group (2 months of 3R4F exposure followed by fresh air or pMRTP for up to 5 months respectively). 3R4F smoke induced the typical adaptive changes in the airways, as well as inflammation in the lung, associated with emphysematous changes (impaired pulmonary function and alveolar damage). At nicotine-matched exposure concentrations of pMRTP aerosol, no signs of lung inflammation and emphysema were observed. Both the cessation and switching groups showed a similar reversal of inflammatory responses and no progression of initial emphysematous changes. A significant impact on biological processes, including COPD-related inflammation, apoptosis, and proliferation, was identified in 3R4F-exposed, but not in pMRTP-exposed lungs. Smoking cessation or switching reduced these perturbations to near sham-exposed levels. In conclusion, the mouse model indicated retarded disease progression upon cessation or switching to pMRTP which alone had no adverse effects.

BackgroundHigh-throughput measurement technologies such as microarrays provide complex datasets reflecting mechanisms perturbed in an experiment, typically a treatment vs. control design. Analysis of these information rich data can be guided based on a priori knowledge, such as networks or set of related proteins or genes. Among those, cause-and-effect network models are becoming increasingly popular and more than eighty such models, describing processes involved in cell proliferation, cell fate, cell stress, and inflammation have already been published. A meaningful systems toxicology approach to study the response of a cell system, or organism, exposed to bio-active substances requires a quantitative measure of dose-response at network level, to go beyond the differential expression of single genes.ResultsWe developed a method that quantifies network response in an interpretable manner. It fully exploits the (signed graph) structure of cause-and-effect networks models to integrate and mine transcriptomics measurements. The presented approach also enables the extraction of network-based signatures for predicting a phenotype of interest. The obtained signatures are coherent with the underlying network perturbation and can lead to more robust predictions across independent studies. The value of the various components of our mathematically coherent approach is substantiated using several in vivo and in vitro transcriptomics datasets. As a proof-of-principle, our methodology was applied to unravel mechanisms related to the efficacy of a specific anti-inflammatory drug in patients suffering from ulcerative colitis. A plausible mechanistic explanation of the unequal efficacy of the drug is provided. Moreover, by utilizing the underlying mechanisms, an accurate and robust network-based diagnosis was built to predict the response to the treatment.ConclusionThe presented framework efficiently integrates transcriptomics data and “cause and effect” network models to enable a mathematically coherent framework from quantitative impact assessment and data interpretation to patient stratification for diagnosis purposes.

Smoking cigarettes is a major risk factor in the development and progression of cardiovascular disease (CVD) and chronic obstructive pulmonary disease (COPD). Modified risk tobacco products (MRTPs) are being developed to reduce smoking-related health risks. The goal of this study was to investigate hallmarks of COPD and CVD over an 8-month period in apolipoprotein E-deficient mice exposed to conventional cigarette smoke (CS) or to the aerosol of a candidate MRTP, tobacco heating system (THS) 2.2. In addition to chronic exposure, cessation or switching to THS2.2 after 2 months of CS exposure was assessed. Engaging a systems toxicology approach, exposure effects were investigated using physiology and histology combined with transcriptomics, lipidomics, and proteomics. CS induced nasal epithelial hyperplasia and metaplasia, lung inflammation, and emphysematous changes (impaired pulmonary function and alveolar damage). Atherogenic effects of CS exposure included altered lipid profiles and aortic plaque formation. Exposure to THS2.2 aerosol (nicotine concentration matched to CS, 29.9 mg/m3) neither induced lung inflammation or emphysema nor did it consistently change the lipid profile or enhance the plaque area. Cessation or switching to THS2.2 reversed the inflammatory responses and halted progression of initial emphysematous changes and the aortic plaque area. Biological processes, including senescence, inflammation, and proliferation, were significantly impacted by CS but not by THS2.2 aerosol. Both, cessation and switching to THS2.2 reduced these perturbations to almost sham exposure levels. In conclusion, in this mouse model cessation or switching to THS2.2 retarded the progression of CS-induced atherosclerotic and emphysematous changes, while THS2.2 aerosol alone had minimal adverse effects.

The lung cancer dataset is available from Gene Expression Omnibus (accession, GSE43580). The maPredictDSC R package implementing the approach of the best overall team is available at www.bioconductor.org or http://bioinformaticsprb.med.wayne.edu/.