Graphical Abstract Highlights d Implementing FAIR data standards requires identification of experimental confounders d Five labs performed the same experiment on mammalian cells and compared results d Several factors affecting reproducibility were explored d Biological context had an unexpected impact on the robustness of cell-based assays

Most cancer cells harbor multiple drivers whose epistasis and interactions with expression context clouds drug and drug combination sensitivity prediction. We constructed a mechanistic computational model that is context-tailored by omics data to capture regulation of stochastic proliferation and death by pan-cancer driver pathways. Simulations and experiments explore how the coordinated dynamics of RAF/MEK/ERK and PI-3K/AKT kinase activities in response to synergistic mitogen or drug combinations control cell fate in a specific cellular context. In this MCF10A cell context, simulations suggest that synergistic ERK and AKT inhibitor-induced death is likely mediated by BIM rather than BAD, which is supported by prior experimental studies. AKT dynamics explain S-phase entry synergy between EGF and insulin, but simulations suggest that stochastic ERK, and not AKT, dynamics seem to drive cell-to-cell proliferation variability, which in simulations is predictable from pre-stimulus fluctuations in C-Raf/B-Raf levels. Simulations suggest MEK alteration negligibly influences transformation, consistent with clinical data. Tailoring the model to an alternate cell expression and mutation context, a glioma cell line, allows prediction of increased sensitivity of cell death to AKT inhibition. Our model mechanistically interprets context-specific landscapes between driver pathways and cell fates, providing a framework for designing more rational cancer combination therapy.

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Lung inflammation in premature infants contributes to the development of bronchopulmonary dysplasia (BPD), a chronic lung disease with long-term sequelae. Pilot studies administering budesonide suspended in surfactant have found reduced BPD without the apparent adverse effects that occur with systemic dexamethasone therapy. Our objective was to determine budesonide potency, stability, and antiinflammatory effects in human fetal lung. We cultured explants of second-trimester fetal lung with budesonide or dexamethasone and used microscopy, immunoassays, RNA sequencing, liquid chromatography/tandem mass spectrometry, and pulsating bubble surfactometry. Budesonide suppressed secreted chemokines IL-8 and CCL2 (MCP-1) within 4 hours, reaching a 90% decrease at 12 hours, which was fully reversed 72 hours after removal of the steroid. Half-maximal effects occurred at 0.04-0.05 nM, representing a fivefold greater potency than for dexamethasone. Budesonide significantly induced 3.6% and repressed 2.8% of 14,500 sequenced mRNAs by 1.6-to 95-fold, including 119 genes that contribute to the glucocorticoid inflammatory transcriptome; some are known targets of nuclear factor-kB. By global proteomics, 22 secreted inflammatory proteins were hormonally regulated. Two glucocorticoid-regulated genes of interest because of their association with lung disease are CHI3L1 and IL1RL1. Budesonide retained activity in the presence of surfactant and did not alter its surface properties. There was some formation of palmitate-budesonide in lung tissue but no detectable metabolism to inactive 16a-hydroxy prednisolone. We concluded that budesonide is a potent and stable antiinflammatory glucocorticoid in human fetal lung in vitro, supporting a beneficial antiinflammatory response to lung-targeted budesonide:surfactant treatment of infants for the prevention of BPD.

Background Glioblastoma (GBM) remains a largely incurable disease as current therapy fails to target the invasive nature of GBM growth in disease progression and recurrence. Here we use the FDA-approved drug and small molecule Hippo inhibitor Verteporfin to target YAP-TEAD activity, known to mediate convergent aspects of tumor invasion/metastasis, and assess the drug’s efficacy and survival benefit in GBM models. Methods Up to eight low-passage patient-derived GBM cell lines with distinct genomic drivers, including three primary/recurrent pairs, were treated with Verteporfin or vehicle to assess in-vitro effects on proliferation, migration, YAP-TEAD activity, and transcriptomics. Patient-derived orthotopic xenograft models (PDX) were used to assess Verteporfin’s brain penetrance and effects on tumor burden and survival. Results Verteporfin treatment disturbed YAP/TAZ-TEAD activity; disrupted transcriptome signatures related to invasion, epithelial-to-mesenchymal, and proneural-to-mesenchymal transition, phenocopying TEAD1-knockout effects; and impaired tumor migration/invasion dynamics across primary and recurrent GBM lines. In an aggressive orthotopic PDX GBM model, short-term Verteporfin treatment consistently diminished core and infiltrative tumor burden, which was associated with decreased tumor expression of Ki67, nuclear YAP, TEAD1, and TEAD-associated targets EGFR, CDH2 and ITGB1. Finally, long-term Verteporfin treatment appeared non-toxic and conferred survival benefit compared to vehicle in two PDX models: as monotherapy in primary (de-novo) GBM and in combination with Temozolomide chemoradiation in recurrent GBM, where VP treatment associated with increased MGMT methylation. Conclusions We demonstrate combined anti-invasive and anti-proliferative efficacy for Verteporfin with survival benefit in preclinical GBM models, indicating potential therapeutic value of this already FDA-approved drug if repurposed for glioblastoma patients.

Objective To identify genes affected by advancing gestation and racial/ethnic origin in human ductus arteriosus (DA). Study design We collected three sets of DA tissue (n=93, n=89, n=91; total = 273 fetuses) from second trimester pregnancies. We examined four genes, with DNA polymorphisms that distribute along racial lines, to identify "Caucasian" and "Non-Caucasian" DA. We used RT-PCR to measure RNA expression of 48 candidate genes involved in functional closure of the DA, and used multivariable regression analyses to examine the relationships between advancing gestation, "Non-Caucasian" race, and gene expression. Results Mature gestation and Non-Caucasian race are significant predictors for identifying infants who will close their patent DA when treated with indomethacin. Advancing gestation consistently altered gene expression in pathways involved with oxygen-induced constriction (e.g., calcium-channels, potassium-channels, and endothelin signaling), contractile protein maturation, tissue remodeling, and prostaglandin and nitric oxide signaling in all three tissue sets. None of the pathways involved with oxygen-induced constriction appeared to be altered in "Non-Caucasian" DA. Two genes, SLCO2A1 and NOS3, (involved with prostaglandin reuptake/metabolism and nitric oxide production, respectively) were consistently decreased in "Non-Caucasian" DA. Conclusions Prostaglandins and nitric oxide are the most important vasodilators opposing DA closure. Indomethacin inhibits prostaglandin production, but not nitric oxide production. Because decreased SLCO2A1 and NOS3 expression can lead to increased prostaglandin and decreased nitric oxide concentrations, we speculate that prostaglandin-mediated vasodilation may play a more dominant role in maintaining the "Non-Caucasian" PDA, making it more likely to close when inhibited by indomethacin.

Monotherapy clinical trials with mutation-targeted kinase inhibitors, despite some success in other cancers, have yet to impact glioblastoma (GBM). Besides insufficient blood-brain barrier penetration, combinations are key to overcoming obstacles such as intratumoral heterogeneity, adaptive resistance, and the epistatic nature of tumor genomics that cause mutation-targeted therapies to fail. With now hundreds of potential drugs, exploring the combination space clinically and preclinically is daunting. We are building a simulation-based approach that integrates patient-specific data with a mechanistic computational model of pan-cancer driver pathways (receptor tyrosine kinases, RAS/RAF/ERK, PI3K/AKT/mTOR, cell cycle, apoptosis, and DNA damage) to prioritize drug combinations by their simulated effects on tumor cell proliferation and death. Here we illustrate a first step, tailoring the model to 14 GBM patients from The Cancer Genome Atlas defined by an mRNA-seq transcriptome, and then simulating responses to three promiscuous FDA-approved kinase inhibitors (bosutinib, ibrutinib, and cabozantinib) with evidence for blood-brain barrier penetration. The model captures binding of the drug to primary targets and off-targets based on published affinity data and simulates responses of 100 heterogeneous tumor cells within a patient. Single drugs are marginally effective or even counterproductive. Common copy number alterations (PTEN loss, EGFR amplification, and NF1 loss) have a negligible correlation with single-drug or combination efficacy, reinforcing the importance of postgenetic approaches that account for kinase inhibitor promiscuity to match drugs to patients. Drug combinations tend to be either cytostatic or cytotoxic, but seldom both, highlighting the need for considering targeted and nontargeted therapy. Although we focus on GBM, the approach is generally applicable.

Fluorescence-based western blots are quantitative in principal, but require determining linear range for each antibody. Here, we use microwestern array to rapidly evaluate suitable conditions for quantitative western blotting, with up to 192 antibody/dilution/replicate combinations on a single standard size gel with a seven-point, two-fold lysate dilution series (~100-fold range). Pilot experiments demonstrate a high proportion of investigated antibodies (17/24) are suitable for quantitative use; however this sample of antibodies is not yet comprehensive across companies, molecular weights, and other important antibody properties, so the ubiquity of this property cannot yet be determined. In some cases microwestern struggled with higher molecular weight membrane proteins, so the technique may not be uniformly applicable to all validation tasks. Linear range for all validated antibodies is at least 8-fold, and up to two orders of magnitude. Phospho-specific and total antibodies do not have discernable trend differences in linear range or limit of detection. Total antibodies generally required higher working concentrations, but more comprehensive antibody panels are required to better establish whether this trend is general or not. Importantly, we demonstrate that results from microwestern analyses scale to normal “macro” western for a subset of antibodies.