Nano-Electrochemical Characterization of a 3D Bioprinted Cervical Tumor Model.

Current cancer research is limited by the availability of reliable in vivo and in vitro models that are able to reproduce the fundamental hallmarks of cancer. Animal experimentation is of paramount importance in the progress of research, but it is becoming more evident that it has several limitations due to the numerous differences between animal tissues and real, in vivo human tissues. 3D bioprinting techniques have become an attractive tool for many basic and applied research fields. Concerning cancer, this technology has enabled the development of three-dimensional in vitro tumor models that recreate the characteristics of real tissues and look extremely promising for studying cancer cell biology. As 3D bioprinting is a relatively recently developed technique, there is still a lack of characterization of the chemical cellular microenvironment of 3D bioprinted constructs. In this work, we fabricated a cervical tumor model obtained by 3D bioprinting of HeLa cells in an alginate-based matrix. Characterization of the spheroid population obtained as a function of culturing time was performed by phase-contrast and confocal fluorescence microscopies. Scanning electrochemical microscopy and platinum nanoelectrodes were employed to characterize oxygen concentrations-a fundamental characteristic of the cellular microenvironment-with a high spatial resolution within the 3D bioprinted cervical tumor model; we also demonstrated that the diffusion of a molecular model of drugs in the 3D bioprinted construct, in which the spheroids were embedded, could be measured quantitatively over time using scanning electrochemical microscopy.

Data-driven learning of narcosis mode of action identifies a CNS transcriptional signature shared between whole organism Caenorhabditis elegans and a fish gill cell line.

With the large numbers of man-made chemicals produced and released in the environment, there is a need to provide assessments on their potential effects on environmental safety and human health. Current regulatory frameworks rely on a mix of both hazard and risk-based approaches to make safety decisions, but the large number of chemicals in commerce combined with an increased need to conduct assessments in the absence of animal testing makes this increasingly challenging. This challenge is catalysing the use of more mechanistic knowledge in safety assessment from both in silico and in vitro approaches in the hope that this will increase confidence in being able to identify modes of action (MoA) for the chemicals in question. Here we approach this challenge by testing whether a functional genomics approach in C. elegans and in a fish cell line can identify molecular mechanisms underlying the effects of narcotics, and the effects of more specific acting toxicants. We show that narcosis affects the expression of neuronal genes associated with CNS function in C. elegans and in a fish cell line. Overall, we believe that our study provides an important step in developing mechanistically relevant biomarkers which can be used to screen for hazards, and which prevent the need for repeated animal or cross-species comparisons for each new chemical.

The HERITAGE Family Study: A Review of the Effects of Exercise Training on Cardiometabolic Health, with Insights into Molecular Transducers.

The aim of the HERITAGE Family Study was to investigate individual differences in response to a standardized endurance exercise program, the role of familial aggregation, and the genetics of response levels of cardiorespiratory fitness and cardiovascular disease and diabetes risk factors. Here we summarize the findings and their potential implications for cardiometabolic health and cardiorespiratory fitness. It begins with overviews of background and planning, recruitment, testing and exercise program protocol, quality control measures, and other relevant organizational issues. A summary of findings is then provided on cardiorespiratory fitness, exercise hemodynamics, insulin and glucose metabolism, lipid and lipoprotein profiles, adiposity and abdominal visceral fat, blood levels of steroids and other hormones, markers of oxidative stress, skeletal muscle morphology and metabolic indicators, and resting metabolic rate. These summaries document the extent of the individual differences in response to a standardized and fully monitored endurance exercise program and document the importance of familial aggregation and heritability level for exercise response traits. Findings from genomic markers, muscle gene expression studies, and proteomic and metabolomics explorations are reviewed, along with lessons learned from a bioinformatics-driven analysis pipeline. The new opportunities being pursued in integrative -omics and physiology have extended considerably the expected life of HERITAGE and are being discussed in relation to the original conceptual model of the study.

Alteration of barrier properties, stratum corneum ceramides and microbiome composition in response to lotion application on cosmetic dry skin.

Xerosis, commonly referred to as dry skin, is a common dermatological condition affecting almost a third of the population. Successful treatment of the condition traditionally involves the application of cosmetic products facilitating the moisturisation of the skin with a range of ingredients including glycerol and fatty acids. While the effectiveness of these treatments is not in question, limited information exists on the impact on the skin microbiome following use of these products and the improvement in skin hydration. Here, we describe improvements in skin barrier properties together with increased levels of cholesterol, ceramides and long-chain fatty acids following application of Body Lotion. Concomitant alterations in the skin microbiome are also seen via 16S rRNA metataxonomics, in combination with both traditional and novel informatics analysis. Following 5 weeks of lotion use, beneficial skin bacteria are increased, with improvements in microbiome functional potential, and increases in pathways associated with biosynthesis of multiple long chain fatty acids.

Genome-wide chromosomal association of Upf1 is linked to Pol II transcription in Schizosaccharomyces pombe.

Although the RNA helicase Upf1 has hitherto been examined mostly in relation to its cytoplasmic role in nonsense mediated mRNA decay (NMD), here we report high-throughput ChIP data indicating genome-wide association of Upf1 with active genes in Schizosaccharomyces pombe. This association is RNase sensitive, correlates with Pol II transcription and mRNA expression levels. Changes in Pol II occupancy were detected in a Upf1 deficient (upf1Δ) strain, prevalently at genes showing a high Upf1 relative to Pol II association in wild-type. Additionally, an increased Ser2 Pol II signal was detected at all highly transcribed genes examined by ChIP-qPCR. Furthermore, upf1Δ cells are hypersensitive to the transcription elongation inhibitor 6-azauracil. A significant proportion of the genes associated with Upf1 in wild-type conditions are also mis-regulated in upf1Δ. These data envisage that by operating on the nascent transcript, Upf1 might influence Pol II phosphorylation and transcription.

Genomics and transcriptomics landscapes associated to changes in insulin sensitivity in response to endurance exercise training.

Despite good adherence to supervised endurance exercise training (EET), some individuals experience no or little improvement in peripheral insulin sensitivity. The genetic and molecular mechanisms underlying this phenomenon are currently not understood. By investigating genome-wide variants associated with baseline and exercise-induced changes (∆) in insulin sensitivity index (Si) in healthy volunteers, we have identified novel candidate genes whose mouse knockouts phenotypes were consistent with a causative effect on Si. An integrative analysis of functional genomic and transcriptomic profiles suggests genetic variants have an aggregate effect on baseline Si and ∆Si, focused around cholinergic signalling, including downstream calcium and chemokine signalling. The identification of calcium regulated MEF2A transcription factor as the most statistically significant candidate driving the transcriptional signature associated to ∆Si further strengthens the relevance of calcium signalling in EET mediated Si response.

Experimental and computational modeling for signature and biomarker discovery of renal cell carcinoma progression.

BACKGROUND: Renal Cell Carcinoma (RCC) is difficult to treat with 5-year survival rate of 10% in metastatic patients. Main reasons of therapy failure are lack of validated biomarkers and scarce knowledge of the biological processes occurring during RCC progression. Thus, the investigation of mechanisms regulating RCC progression is fundamental to improve RCC therapy. METHODS: In order to identify molecular markers and gene processes involved in the steps of RCC progression, we generated several cell lines of higher aggressiveness by serially passaging mouse renal cancer RENCA cells in mice and, concomitantly, performed functional genomics analysis of the cells. Multiple cell lines depicting the major steps of tumor progression (including primary tumor growth, survival in the blood circulation and metastatic spread) were generated and analyzed by large-scale transcriptome, genome and methylome analyses. Furthermore, we performed clinical correlations of our datasets. Finally we conducted a computational analysis for predicting the time to relapse based on our molecular data. RESULTS: Through in vivo passaging, RENCA cells showed increased aggressiveness by reducing mice survival, enhancing primary tumor growth and lung metastases formation. In addition, transcriptome and methylome analyses showed distinct clustering of the cell lines without genomic variation. Distinct signatures of tumor aggressiveness were revealed and validated in different patient cohorts. In particular, we identified SAA2 and CFB as soluble prognostic and predictive biomarkers of the therapeutic response. Machine learning and mathematical modeling confirmed the importance of CFB and SAA2 together, which had the highest impact on distant metastasis-free survival. From these data sets, a computational model predicting tumor progression and relapse was developed and validated. These results are of great translational significance. CONCLUSION: A combination of experimental and mathematical modeling was able to generate meaningful data for the prediction of the clinical evolution of RCC.

Systems analysis of miRNA biomarkers to inform drug safety.

microRNAs (miRNAs or miRs) are short non-coding RNA molecules which have been shown to be dysregulated and released into the extracellular milieu as a result of many drug and non-drug-induced pathologies in different organ systems. Consequently, circulating miRs have been proposed as useful biomarkers of many disease states, including drug-induced tissue injury. miRs have shown potential to support or even replace the existing traditional biomarkers of drug-induced toxicity in terms of sensitivity and specificity, and there is some evidence for their improved diagnostic and prognostic value. However, several pre-analytical and analytical challenges, mainly associated with assay standardization, require solutions before circulating miRs can be successfully translated into the clinic. This review will consider the value and potential for the use of circulating miRs in drug-safety assessment and describe a systems approach to the analysis of the miRNAome in the discovery setting, as well as highlighting standardization issues that at this stage prevent their clinical use as biomarkers. Highlighting these challenges will hopefully drive future research into finding appropriate solutions, and eventually circulating miRs may be translated to the clinic where their undoubted biomarker potential can be used to benefit patients in rapid, easy to use, point-of-care test systems.

Modeling the metabolic profile of Mytilus edulis reveals molecular signatures linked to gonadal development, sex and environmental site.

The monitoring of anthropogenic chemicals in the aquatic environment including their potential effects on aquatic organisms, is important for protecting life under water, a key sustainable development goal. In parallel with monitoring the concentrations of chemicals of concern, sentinel species are often used to investigate the biological effects of contaminants. Among these, bivalve molluscs such as mussels are filter-feeding and sessile, hence an excellent model system for measuring localized pollution. This study investigates the relationship between the metabolic state of the blue mussel (Mytilus edulis) and its physiology in different environments. We developed a computational model based on a reference site (relatively unpolluted) and integrated seasonal dynamics of metabolite relative concentrations with key physiological indicators and environmental parameters. The analysis of the model revealed that changes in metabolite levels during an annual cycle are influenced by water temperature and are linked to gonadal development. This work supports the importance of data-driven biology and its potential in environmental monitoring.

The dipeptide prolyl-hydroxyproline promotes cellular homeostasis and lamellipodia-driven motility via active ß1-integrin in adult tendon cells.

Collagen-derived hydroxyproline (Hyp)-containing peptides have a variety of biological effects on cells. These bioactive collagen peptides are locally generated by the degradation of endogenous collagen in response to injury. However, no comprehensive study has yet explored the functional links between Hyp-containing peptides and cellular behavior. Here, we show that the dipeptide prolyl-4-hydroxyproline (Pro-Hyp) exhibits pronounced effects on mouse tendon cells. Pro-Hyp promotes differentiation/maturation of tendon cells with modulation of lineage-specific factors and induces significant chemotactic activity in vitro. In addition, Pro-Hyp has profound effects on cell proliferation, with significantly upregulated extracellular signal-regulated kinase phosphorylation and extracellular matrix production and increased type I collagen network organization. Using proteomics, we have predicted molecular transport, cellular assembly and organization, and cellular movement as potential linked-network pathways that could be altered in response to Pro-Hyp. Mechanistically, cells treated with Pro-Hyp demonstrate increased directional persistence and significantly increased directed motility and migration velocity. They are accompanied by elongated lamellipodial protrusions with increased levels of active ß1-integrin-containing focal contacts, as well as reorganization of thicker peripheral F-actin fibrils. Pro-Hyp-mediated chemotactic activity is significantly reduced (p < 0.001) in cells treated with the mitogen-activated protein kinase kinase 1/2 inhibitor PD98059 or the α5ß1-integrin antagonist ATN-161. Furthermore, ATN-161 significantly inhibits uptake of Pro-Hyp into adult tenocytes. Thus, our findings document the molecular basis of the functional benefits of the Pro-Hyp dipeptide in cellular behavior. These dynamic properties of collagen-derived Pro-Hyp dipeptide could lead the way to its application in translational medicine.

Assessing technical and biological variation in SWATH-MS-based proteomic analysis of chronic lymphocytic leukaemia cells.

Chronic lymphocytic leukaemia (CLL) exhibits variable clinical course and response to therapy, but the molecular basis of this variability remains incompletely understood. Data independent acquisition (DIA)-MS technologies, such as SWATH (Sequential Windowed Acquisition of all THeoretical fragments), provide an opportunity to study the pathophysiology of CLL at the proteome level. Here, a CLL-specific spectral library (7736 proteins) is described alongside an analysis of sample replication and data handling requirements for quantitative SWATH-MS analysis of clinical samples. The analysis was performed on 6 CLL samples, incorporating biological (IGHV mutational status), sample preparation and MS technical replicates. Quantitative information was obtained for 5169 proteins across 54 SWATH-MS acquisitions: the sources of variation and different computational approaches for batch correction were assessed. Functional enrichment analysis of proteins associated with IGHV mutational status showed significant overlap with previous studies based on gene expression profiling. Finally, an approach to perform statistical power analysis in proteomics studies was implemented. This study provides a valuable resource for researchers working on the proteomics of CLL. It also establishes a sound framework for the design of sufficiently powered clinical proteomics studies. Indeed, this study shows that it is possible to derive biologically plausible hypotheses from a relatively small dataset.

MMP13 and TIMP1 are functional markers for two different potential modes of action by mesenchymal stem/stromal cells when treating osteoarthritis.

Mesenchymal stem cells (MSCs) have been investigated as a potential injectable therapy for the treatment of knee osteoarthritis, with some evidence of success in preliminary human trials. However, optimization and scale-up of this therapeutic approach depends on the identification of functional markers that are linked to their mechanism of action. One possible mechanism is through their chondrogenic differentiation and direct role in neo-cartilage synthesis. Alternatively, they could remain undifferentiated and act through the release of trophic factors that stimulate endogenous repair processes within the joint. Here, we show that extensive in vitro aging of bone marrow-derived human MSCs leads to loss of chondrogenesis but no reduction in trophic repair, thereby separating out the two modes of action. By integrating transcriptomic and proteomic data using Ingenuity Pathway Analysis, we found that reduced chondrogenesis with passage is linked to downregulation of the FOXM1 signaling pathway while maintenance of trophic repair is linked to CXCL12. In an attempt at developing functional markers of MSC potency, we identified loss of mRNA expression for MMP13 as correlating with loss of chondrogenic potential of MSCs and continued secretion of high levels of TIMP1 protein as correlating with the maintenance of trophic repair capacity. Since an allogeneic injectable osteoar therapy would require extensive cell expansion in vitro, we conclude that early passage MMP13+ , TIMP1-secretinghigh MSCs should be used for autologous OA therapies designed to act through engraftment and chondrogenesis, while later passage MMP13- , TIMP1-secretinghigh MSCs could be exploited for allogeneic OA therapies designed to act through trophic repair.

The Sodium Channel B4-Subunits are Dysregulated in Temporal Lobe Epilepsy Drug-Resistant Patients.

Temporal lobe epilepsy (TLE) is the most common type of partial epilepsy referred for surgery due to antiepileptic drug (AED) resistance. A common molecular target for many of these drugs is the voltage-gated sodium channel (VGSC). The VGSC consists of four domains of pore-forming α-subunits and two auxiliary ß-subunits, several of which have been well studied in epileptic conditions. However, despite the ß4-subunits' role having been reported in some neurological conditions, there is little research investigating its potential significance in epilepsy. Therefore, the purpose of this work was to assess the role of SCN4ß in epilepsy by using a combination of molecular and bioinformatics approaches. We first demonstrated that there was a reduction in the relative expression of SCN4B in the drug-resistant TLE patients compared to non-epileptic control specimens, both at the mRNA and protein levels. By analyzing a co-expression network in the neighborhood of SCN4B we then discovered a linkage between the expression of this gene and K+ channels activated by Ca2+, or K+ two-pore domain channels. Our approach also inferred several potential effector functions linked to variation in the expression of SCN4B. These observations support the hypothesis that SCN4B is a key factor in AED-resistant TLE, which could help direct both the drug selection of TLE treatments and the development of future AEDs.

Mapping the Transcriptional and Fitness Landscapes of a Pathogenic E. coli Strain: The Effects of Organic Acid Stress under Aerobic and Anaerobic Conditions.

Several methods are available to probe cellular responses to external stresses at the whole genome level. RNAseq can be used to measure changes in expression of all genes following exposure to stress, but gives no information about the contribution of these genes to an organism's ability to survive the stress. The relative contribution of each non-essential gene in the genome to the fitness of the organism under stress can be obtained using methods that use sequencing to estimate the frequencies of members of a dense transposon library grown under different conditions, for example by transposon-directed insertion sequencing (TraDIS). These two methods thus probe different aspects of the underlying biology of the organism. We were interested to determine the extent to which the data from these two methods converge on related genes and pathways. To do this, we looked at a combination of biologically meaningful stresses. The human gut contains different organic short-chain fatty acids (SCFAs) produced by fermentation of carbon compounds, and Escherichia coli is exposed to these in its passage through the gut. Their effect is likely to depend on both the ambient pH and the level of oxygen present. We, therefore, generated RNAseq and TraDIS data on a uropathogenic E. coli strain grown at either pH 7 or pH 5.5 in the presence or absence of three SCFAs (acetic, propionic and butyric), either aerobically or anaerobically. Our analysis identifies both known and novel pathways as being likely to be important under these conditions. There is no simple correlation between gene expression and fitness, but we found a significant overlap in KEGG pathways that are predicted to be enriched following analysis of the data from the two methods, and the majority of these showed a fitness signature that would be predicted from the gene expression data, assuming expression to be adaptive. Genes which are not in the E. coli core genome were found to be particularly likely to show a positive correlation between level of expression and contribution to fitness.

Vision of a near future: Bridging the human health-environment divide. Toward an integrated strategy to understand mechanisms across species for chemical safety assessment.

There is a growing recognition that application of mechanistic approaches to understand cross-species shared molecular targets and pathway conservation in the context of hazard characterization, provide significant opportunities in risk assessment (RA) for both human health and environmental safety. Specifically, it has been recognized that a more comprehensive and reliable understanding of similarities and differences in biological pathways across a variety of species will better enable cross-species extrapolation of potential adverse toxicological effects. Ultimately, this would also advance the generation and use of mechanistic data for both human health and environmental RA. A workshop brought together representatives from industry, academia and government to discuss how to improve the use of existing data, and to generate new NAMs data to derive better mechanistic understanding between humans and environmentally-relevant species, ultimately resulting in holistic chemical safety decisions. Thanks to a thorough dialogue among all participants, key challenges, current gaps and research needs were identified, and potential solutions proposed. This discussion highlighted the common objective to progress toward more predictive, mechanistically based, data-driven and animal-free chemical safety assessments. Overall, the participants recognized that there is no single approach which would provide all the answers for bridging the gap between mechanism-based human health and environmental RA, but acknowledged we now have the incentive, tools and data availability to address this concept, maximizing the potential for improvements in both human health and environmental RA.

Computationally predicted gene regulatory networks in molluscan biomineralization identify extracellular matrix production and ion transportation pathways.

MOTIVATION: The molecular processes regulating molluscan shell production remain relatively uncharacterized, despite the clear evolutionary and societal importance of biomineralization. RESULTS: Here we built the first computationally predicted gene regulatory network (GRN) for molluscan biomineralization using Antarctic clam (Laternula elliptica) mantle gene expression data produced over an age-categorized shell damage-repair time-course. We used previously published in vivo in situ hybridization expression data to ground truth gene interactions predicted by the GRN and show that candidate biomineralization genes from different shell layers, and hence microstructures, were connected in unique modules. We characterized two biomineralization modules of the GRN and hypothesize that one module is responsible for translating the extracellular proteins required for growing, repairing or remodelling the nacreous shell layer, whereas the second module orchestrates the transport of both ions and proteins to the shell secretion site, which are required during normal shell growth, and repair. Our findings demonstrate that unbiased computational methods are particularly valuable for studying fundamental biological processes and gene interactions in non-model species where rich sources of gene expression data exist, but annotation rates are poor and the ability to carry out true functional tests are still lacking. AVAILABILITY AND IMPLEMENTATION: The raw RNA-Seq data is freely available for download from NCBI SRA (Accession: PRJNA398984), the assembled and annotated transcriptome can be viewed and downloaded from molluscDB (ensembl.molluscdb.org) and in addition, the assembled transcripts, reconstructed GRN, modules and detailed annotations are all available as Supplementary Files. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A novel panel of differentially-expressed microRNAs in breast cancer brain metastasis may predict patient survival.

Breast cancer brain metastasis (BCBM) is an area of unmet clinical need. MicroRNAs (miRNAs) have been linked to the metastatic process in breast cancer (BC). In this study, we aim to determine differentially-expressed miRNAs utilising primary BCs that did not relapse (BCNR, n = 12), primaries that relapsed (BCR) and their paired (n = 40 pairs) brain metastases (BM) using the NanoString™ nCounter™ miRNA Expression Assays. Significance analysis of microarrays identified 58 and 11 differentially-expressed miRNAs between BCNR vs BCR and BCR vs BM respectively and pathway analysis revealed enrichment for genes involved in invasion and metastasis. Four miRNAs, miR-132-3p, miR-199a-5p, miR-150-5p and miR-155-5p, were differentially-expressed within both cohorts (BCNR-BCR, BCR-BM) and receiver-operating characteristic curve analysis (p = 0.00137) and Kaplan-Meier survival method (p = 0.0029, brain metastasis-free survival; p = 0.0007, overall survival) demonstrated their potential use as prognostic markers. Ingenuity pathway enrichment linked them to the MET oncogene, and the cMET protein was overexpressed in the BCR (p < 0.0001) and BM (p = 0.0008) cases, compared to the BCNRs. The 4-miRNAs panel identified in this study could be potentially used to distinguish BC patients with an increased risk of developing BCBM and provide potential novel therapeutic targets, whereas cMET-targeting warrants further investigation in the treatment of BCBM.

Deciphering the complex role of thrombospondin-1 in glioblastoma development.

We undertook a systematic study focused on the matricellular protein Thrombospondin-1 (THBS1) to uncover molecular mechanisms underlying the role of THBS1 in glioblastoma (GBM) development. THBS1 was found to be increased with glioma grades. Mechanistically, we show that the TGFß canonical pathway transcriptionally regulates THBS1, through SMAD3 binding to the THBS1 gene promoter. THBS1 silencing inhibits tumour cell invasion and growth, alone and in combination with anti-angiogenic therapy. Specific inhibition of the THBS1/CD47 interaction using an antagonist peptide decreases cell invasion. This is confirmed by CD47 knock-down experiments. RNA sequencing of patient-derived xenograft tissue from laser capture micro-dissected peripheral and central tumour areas demonstrates that THBS1 is one of the gene with the highest connectivity at the tumour borders. All in all, these data show that TGFß1 induces THBS1 expression via Smad3 which contributes to the invasive behaviour during GBM expansion. Furthermore, tumour cell-bound CD47 is implicated in this process.

Systems biology reveals how altered TGFß signalling with age reduces protection against pro-inflammatory stimuli.

Osteoarthritis (OA) is a degenerative condition caused by dysregulation of multiple molecular signalling pathways. Such dysregulation results in damage to cartilage, a smooth and protective tissue that enables low friction articulation of synovial joints. Matrix metalloproteinases (MMPs), especially MMP-13, are key enzymes in the cleavage of type II collagen which is a vital component for cartilage integrity. Transforming growth factor beta (TGFß) can protect against pro-inflammatory cytokine-mediated MMP expression. With age there is a change in the ratio of two TGFß type I receptors (Alk1/Alk5), a shift that results in TGFß losing its protective role in cartilage homeostasis. Instead, TGFß promotes cartilage degradation which correlates with the spontaneous development of OA in murine models. However, the mechanism by which TGFß protects against pro-inflammatory responses and how this changes with age has not been extensively studied. As TGFß signalling is complex, we used systems biology to combine experimental and computational outputs to examine how the system changes with age. Experiments showed that the repressive effect of TGFß on chondrocytes treated with a pro-inflammatory stimulus required Alk5. Computational modelling revealed two independent mechanisms were needed to explain the crosstalk between TGFß and pro-inflammatory signalling pathways. A novel meta-analysis of microarray data from OA patient tissue was used to create a Cytoscape network representative of human OA and revealed the importance of inflammation. Combining the modelled genes with the microarray network provided a global overview into the crosstalk between the different signalling pathways involved in OA development. Our results provide further insights into the mechanisms that cause TGFß signalling to change from a protective to a detrimental pathway in cartilage with ageing. Moreover, such a systems biology approach may enable restoration of the protective role of TGFß as a potential therapy to prevent age-related loss of cartilage and the development of OA.

Chemical hazard prediction and hypothesis testing using quantitative adverse outcome pathways.

Current efforts in chemical safety are focused on utilizing human in vitro or alternative animal data in biological pathway context. However, it remains unclear how biological pathways, and toxicology data developed in that context, can be used to quantitatively facilitate decision-making.  The objective of this work is to determine if hypothesis testing using Adverse Outcome Pathways (AOPs) can provide quantitative chemical hazard predictions.  Current methods for predicting hazards of chemicals in a biological pathway context were extensively reviewed, specific case studies examined and computational modeling used to demonstrate quantitative hazard prediction based on an AOP. Since AOPs are chemically agnostic, we propose that AOPs function as hypotheses for how specific chemicals may cause adverse effects via specific pathways. Three broad approaches were identified for testing the hypothesis with AOPs, semi-quantitative weight of evidence, probabilistic, and mechanistic modeling. We then demonstrate how these approaches could be used to test hypotheses using high throughput in vitro data and alternative animal data. Finally, we discuss standards in development and documentation that would facilitate use in a regulatory context. We conclude that quantitative AOPs provide a flexible hypothesis framework for predicting chemical hazards. It accommodates a wide range of approaches that are useful at many stages and build upon one another to become increasingly quantitative.