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Nuclear factor erythroid-2 related factor 2 (NRF2) encoded by the NFE2L2 gene is a transcription factor critical for protecting cells from chemically-induced oxidative stress. We developed computational procedures to identify chemical modulators of NRF2 in a large database of human microarray data. A gene expression biomarker was built from statistically-filtered gene lists derived from microarray experiments in primary human hepatocytes and cancer cell lines exposed to NRF2-activating chemicals (oltipraz, sulforaphane, CDDO-Im) or in which the NRF2 suppressor Keap1 was knocked down by siRNA. Directionally consistent biomarker genes were further filtered for those dependent on NRF2 using a microarray dataset from cells after NFE2L2 siRNA knockdown. The resulting 143-gene biomarker was evaluated as a predictive tool using the correlation-based Running Fisher algorithm. Using 59 gene expression comparisons from chemically-treated cells with known NRF2 activating potential, the biomarker gave a balanced accuracy of 93%. The biomarker was comprised of many well-known NRF2 target genes (AKR1B10, AKR1C1, NQO1, TXNRD1, SRXN1, GCLC, GCLM), 69% of which were found to be bound directly by NRF2 using ChIP-Seq. NRF2 activity was assessed across ~9840 microarray comparisons from ~1460 studies examining the effects of ~2260 chemicals in human cell lines. A total of 260 and 43 chemicals were found to activate or suppress NRF2, respectively, most of which have not been previously reported to modulate NRF2 activity. Using a NRF2-responsive reporter gene in HepG2 cells, we confirmed the activity of a set of chemicals predicted using the biomarker. The biomarker will be useful for future gene expression screening studies of environmentally-relevant chemicals.

Adaptive stress response pathways play a key role in the switch between adaptation and adversity, and are important in drug-induced liver injury. Previously, we have established an HepG2 fluorescent protein reporter platform to monitor adaptive stress response activation following drug treatment. HepG2 cells are often used in high-throughput primary toxicity screening, but metabolizing capacity in these cells is low and repeated dose toxicity testing inherently difficult. Here, we applied our bacterial artificial chromosome-based GFP reporter cell lines representing Nrf2 activation (Srxn1-GFP and NQO1-GFP), unfolded protein response (BiP-GFP and Chop-GFP), and DNA damage response (p21-GFP and Btg2-GFP) as long-term differentiated 3D liver-like spheroid cultures. All HepG2 GFP reporter lines differentiated into 3D spheroids similar to wild-type HepG2 cells. We systematically optimized the automated imaging and quantification of GFP reporter activity in individual spheroids using high-throughput confocal microscopy with a reference set of DILI compounds that activate these three stress response pathways at the transcriptional level in primary human hepatocytes. A panel of 33 compounds with established DILI liability was further tested in these six 3D GFP reporters in single 48 h treatment or 6 day daily repeated treatment. Strongest stress response activation was observed after 6-day repeated treatment, with the BiP and Srxn1-GFP reporters being most responsive and identified particular severe-DILI-onset compounds. Compounds that showed no GFP reporter activation in two-dimensional (2D) monolayer demonstrated GFP reporter stress response activation in 3D spheroids. Our data indicate that the application of BAC-GFP HepG2 cellular stress reporters in differentiated 3D spheroids is a promising strategy for mechanism-based identification of compounds with liability for DILI.

Ttriple-negative breast cancer (TNBC) is an aggressive and highly metastatic breast cancer subtype. Enhanced TNBC cell motility is a prerequisite of TNBC cell dissemination. Here, we apply an imaging-based RNAi phenotypic cell migration screen using two highly motile TNBC cell lines (Hs578T and MDA-MB-231) to provide a repository of signaling determinants that functionally drive TNBC cell motility. We have screened ~4,200 target genes individually and discovered 133 and 113 migratory modulators of Hs578T and MDA-MB-231, respectively, which are linked to signaling networks predictive for breast cancer progression. The splicing factors PRPF4B and BUD31 and the transcription factor BPTF are essential for cancer cell migration, amplified in human primary breast tumors and associated with metastasis-free survival. Depletion of PRPF4B , BUD31 and BPTF causes primarily down regulation of genes involved in focal adhesion and ECM-interaction pathways. PRPF4B is essential for TNBC metastasis formation in vivo, making PRPF4B a candidate for further drug development. Triple-negative breast cancers (TNBC) have enhanced migratory behaviour. Here, the authors perform a phenotypic imaging-based RNAi screen to identify several genes associated with regulation of migratory phenotypes and show that one of the regulators, PRPF4B , mediates metastasis in TNBC in mice.

Drug-induced liver injury remains a concern during drug treatment and development. There is an urgent need for improved mechanistic understanding and prediction of DILI liabilities using in vitro approaches. We have established and characterized a panel of liver cell models containing mechanism-based fluorescent protein toxicity pathway reporters to quantitatively assess the dynamics of cellular stress response pathway activation at the single cell level using automated live cell imaging. We have systematically evaluated the application of four key adaptive stress pathway reporters for the prediction of DILI liability: SRXN1-GFP (oxidative stress), CHOP-GFP (ER stress/UPR response), p21 (p53-mediated DNA damage-related response) and ICAM1 (NF-κB-mediated inflammatory signaling). 118 FDA-labeled drugs in five human exposure relevant concentrations were evaluated for reporter activation using live cell confocal imaging. Quantitative data analysis revealed activation of single or multiple reporters by most drugs in a concentration and time dependent manner. Hierarchical clustering of time course dynamics and refined single cell analysis allowed the allusion of key events in DILI liability. Concentration response modeling was performed to calculate benchmark concentrations (BMCs). Extracted temporal dynamic parameters and BMCs were used to assess the predictive power of sub-lethal adaptive stress pathway activation. Although cellular adaptive responses were activated by non-DILI and severe-DILI compounds alike, dynamic behavior and lower BMCs of pathway activation were sufficiently distinct between these compound classes. The high-level detailed temporal- and concentration-dependent evaluation of the dynamics of adaptive stress pathway activation adds to the overall understanding and prediction of drug-induced liver liabilities.

Adaptive cellular stress responses are paramount in the healthy control of cell and tissue homeostasis and generally activated during toxicity in a chemical-specific manner. Here, we established a platform containing a panel of distinct adaptive stress response reporter cell lines based on BAC-transgenomics GFP tagging in HepG2 cells. Our current panel of eleven BAC-GFP HepG2 reporters together contains (1) upstream sensors, (2) downstream transcription factors and (3) their respective target genes, representing the oxidative stress response pathway (Keap1/Nrf2/Srxn1), the unfolded protein response in the endoplasmic reticulum (Xbp1/Atf4/BiP/Chop) and the DNA damage response (53bp1/p53/p21). Using automated confocal imaging and quantitative single-cell image analysis, we established that all reporters allowed the time-resolved, sensitive and mode-of-action-specific activation of the individual BAC-GFP reporter cell lines as defined by a panel of pathway-specific training compounds. Implementing the temporal pathway activity information increased the discrimination of training compounds. For a set of >30 hepatotoxicants, the induction of Srxn1, BiP, Chop and p21 BAC-GFP reporters correlated strongly with the transcriptional responses observed in cryopreserved primary human hepatocytes. Together, our data indicate that a phenotypic adaptive stress response profiling platform will allow a high throughput and time-resolved classification of chemical-induced stress responses, thus assisting in the future mechanism-based safety assessment of chemicals.

Drug-induced liver injury (DILI) is an important problem both in the clinic and in the development of new safer medicines. Two pivotal adaptation and survival responses to adverse drug reactions are oxidative stress and cytokine signaling based on the activation of the transcription factors Nrf2 and NF-κB, respectively. Here, we systematically investigated Nrf2 and NF-κB signaling upon DILI-related drug exposure. Transcriptomics analyses of 90 DILI compounds in primary human hepatocytes revealed that a strong Nrf2 activation is associated with a suppression of endogenous NF-κB activity. These responses were translated into quantitative high-content live-cell imaging of induction of a selective Nrf2 target, GFP-tagged Srxn1, and the altered nuclear translocation dynamics of a subunit of NF-κB, GFP-tagged p65, upon TNFR signaling induced by TNFα using HepG2 cells. Strong activation of GFP-Srxn1 expression by DILI compounds typically correlated with suppression of NF-κB nuclear translocation, yet reversely, activation of NF-κB by TNFα did not affect the Nrf2 response. DILI compounds that provided strong Nrf2 activation, including diclofenac, carbamazepine and ketoconazole, sensitized toward TNFα-mediated cytotoxicity. This was related to an adaptive primary protective response of Nrf2, since loss of Nrf2 enhanced this cytotoxic synergy with TNFα, while KEAP1 downregulation was cytoprotective. These data indicate that both Nrf2 and NF-κB signaling may be pivotal in the regulation of DILI. We propose that the NF-κB-inhibiting effects that coincide with a strong Nrf2 stress response likely sensitize liver cells to pro-apoptotic signaling cascades induced by intrinsic cytotoxic pro-inflammatory cytokines.

Introduction Insulin analogues are designed to have improved pharmacokinetic parameters compared to regular human insulin. This provides a sustained control of blood glucose levels in diabetic patients. All novel insulin analogues are tested for their mitogenic side effects, however these assays do not take into account the molecular mode of action of different insulin analogues. Insulin analogues can bind the insulin receptor and the insulin-like growth factor 1 receptor with different affinities and consequently will activate different downstream signaling pathways. Methods Here we used a panel of MCF7 human breast cancer cell lines that selectively express either one of the isoforms of the INSR or the IGF1R. We applied a transcriptomics approach to assess the differential transcriptional programs activated in these cells by either insulin, IGF1 or X10 treatment. Results Based on the differentially expressed genes between insulin versus IGF1 and X10 treatment, we retrieved a mitogenic classifier gene set. Validation by RT-qPCR confirmed the robustness of this gene set. The translational potential of these mitogenic classifier genes was examined in primary human mammary cells and in mammary gland tissue of mice in an in vivo model. The predictive power of the classifier genes was evaluated by testing all commercial insulin analogues in the in vitro model and defined X10 and glargine as the most potent mitogenic insulin analogues. Conclusions We propose that these mitogenic classifier genes can be used to test the mitogenic potential of novel insulin analogues as well as other alternative molecules with an anticipated affinity for the IGF1R.

Drug-induced liver injury (DILI) is an important problem both in the clinic and in the development of new safer medicines. Two pivotal adaptation and survival responses to adverse drug reactions are oxidative stress and cytokine signaling based on the activation of the transcription factors Nrf2 and NF-[kappa]B, respectively. Here, we systematically investigated Nrf2 and NF-[kappa]B signaling upon DILI-related drug exposure. Transcriptomics analyses of 90 DILI compounds in primary human hepatocytes revealed that a strong Nrf2 activation is associated with a suppression of endogenous NF-[kappa]B activity. These responses were translated into quantitative high-content live-cell imaging of induction of a selective Nrf2 target, GFP-tagged Srxn1, and the altered nuclear translocation dynamics of a subunit of NF-[kappa]B, GFP-tagged p65, upon TNFR signaling induced by TNF[alpha] using HepG2 cells. Strong activation of GFP-Srxn1 expression by DILI compounds typically correlated with suppression of NF-[kappa]B nuclear translocation, yet reversely, activation of NF-[kappa]B by TNF[alpha] did not affect the Nrf2 response. DILI compounds that provided strong Nrf2 activation, including diclofenac, carbamazepine and ketoconazole, sensitized toward TNF[alpha]-mediated cytotoxicity. This was related to an adaptive primary protective response of Nrf2, since loss of Nrf2 enhanced this cytotoxic synergy with TNF[alpha], while KEAP1 downregulation was cytoprotective. These data indicate that both Nrf2 and NF-[kappa]B signaling may be pivotal in the regulation of DILI. We propose that the NF-[kappa]B-inhibiting effects that coincide with a strong Nrf2 stress response likely sensitize liver cells to pro-apoptotic signaling cascades induced by intrinsic cytotoxic pro-inflammatory cytokines.

Technological development has led to ever-increasing amounts of data in high-content screening. For utilizing such data in an efficient, thorough, and user-friendly manner we developed the R package H5CellProfiler. H5CellProfiler is based on R packages data.table, ggvis, ggplot2 and shiny. H5CellProfiler launches a browser that allows scientists to analyze large single-cell datasets and make statistical summaries and graphs on their local desktop in a fast and memory-efficient manner. In addition, single-cell track labels are calculated and broken tracks are re-connected based on user-defined thresholds resulting in unique sets of annotated tracks. Competing Interest Statement The authors have declared no competing interest. Footnotes * https://zenodo.org/record/5484432