Multi-targeted kinase inhibition alleviates mTOR inhibitor resistance in triple-negative breast cancer

Purpose

Owing to its genetic heterogeneity and acquired resistance, triple-negative breast cancer (TNBC) is not responsive to single-targeted therapy, causing disproportional cancer-related death worldwide. Combined targeted therapy strategies to block interactive oncogenic signaling networks are being explored for effective treatment of the refractory TNBC subtype.

Methods

A broad kinase inhibitor screen was applied to profile the proliferative responses of TNBC cells, revealing resistance of TNBC cells to inhibition of the mammalian target of rapamycin (mTOR). A systematic drug combination screen was subsequently performed to identify that AEE788, an inhibitor targeting multiple receptor tyrosine kinases (RTKs) EGFR/HER2 and VEGFR, synergizes with selective mTOR inhibitor rapamycin as well as its analogs (rapalogs) temsirolimus and everolimus to inhibit TNBC cell proliferation.

Results

The combination treatment with AEE788 and rapalog effectively inhibits phosphorylation of mTOR and 4EBP1, relieves mTOR inhibition-mediated upregulation of cyclin D1, and maintains suppression of AKT and ERK signaling, thereby sensitizing TNBC cells to the rapalogs. siRNA validation of cheminformatics-based predicted AEE788 targets has further revealed the mTOR interactive RPS6K members (RPS6KA3, RPS6KA6, RPS6KB1, and RPS6KL1) as synthetic lethal targets for rapalog combination treatment.

Conclusions

mTOR signaling is highly activated in TNBC tumors. As single rapalog treatment is insufficient to block mTOR signaling in rapalog-resistant TNBC cells, our results thus provide a potential multi-kinase inhibitor combinatorial strategy to overcome mTOR-targeted therapy resistance in TNBC cells.

Electronic supplementary material

The online version of this article (10.1007/s10549-019-05380-z) contains supplementary material, which is available to authorized users.

Migration rather than proliferation transcriptomic signatures are strongly associated with breast cancer patient survival

The efficacy of prospective cancer treatments is routinely estimated by in vitro cell-line proliferation screens. However, it is unclear whether tumor aggressiveness and patient survival are influenced more by the proliferative or the migratory properties of cancer cells. To address this question, we experimentally measured proliferation and migration phenotypes across more than 40 breast cancer cell-lines. Based on the latter, we built and validated individual predictors of breast cancer proliferation and migration levels from the cells' transcriptomics. We then apply these predictors to estimate the proliferation and migration levels of more than 1000 TCGA breast cancer tumors. Reassuringly, both estimates increase with tumor's aggressiveness, as qualified by its stage, grade, and subtype. However, predicted tumor migration levels are significantly more strongly associated with patient survival than the proliferation levels. We confirmed these findings by conducting siRNA knock-down experiments on the highly migratory MDA-MB-231 cell lines and deriving gene knock-down based proliferation and migration signatures. We show that cytoskeletal drugs might be more beneficial in patients with high predicted migration levels. Taken together, these results testify to the importance of migration levels in determining patient survival.

A kinase inhibitor screen identifies a dual cdc7/CDK9 inhibitor to sensitise triple-negative breast cancer to EGFR-targeted therapy

BACKGROUND

The effective treatment of triple-negative breast cancer (TNBC) remains a profound clinical challenge. Despite frequent epidermal growth factor receptor (EGFR) overexpression and reliance on downstream signalling pathways in TNBC, resistance to EGFR-tyrosine kinase inhibitors (TKIs) remains endemic. Therefore, the identification of targeted agents, which synergise with current therapeutic options, is paramount.

METHODS

Compound-based, high-throughput, proliferation screening was used to profile the response of TNBC cell lines to EGFR-TKIs, western blotting and siRNA transfection being used to examine the effect of inhibitors on EGFR-mediated signal transduction and cellular dependence on such pathways, respectively. A kinase inhibitor combination screen was used to identify compounds that synergised with EGFR-TKIs in TNBC, utilising sulphorhodamine B (SRB) assay as read-out for proliferation. The impact of drug combinations on cell cycle arrest, apoptosis and signal transduction was assessed using flow cytometry, automated live-cell imaging and western blotting, respectively. RNA sequencing was employed to unravel transcriptomic changes elicited by this synergistic combination and to permit identification of the signalling networks most sensitive to co-inhibition.

RESULTS

We demonstrate that a dual cdc7/CDK9 inhibitor, PHA-767491, synergises with multiple EGFR-TKIs (lapatinib, erlotinib and gefitinib) to overcome resistance to EGFR-targeted therapy in various TNBC cell lines. Combined inhibition of EGFR and cdc7/CDK9 resulted in reduced cell proliferation, accompanied by induction of apoptosis, G2-M cell cycle arrest, inhibition of DNA replication and abrogation of CDK9-mediated transcriptional elongation, in contrast to mono-inhibition. Moreover, high expression of cdc7 and RNA polymerase II Subunit A (POLR2A), the direct target of CDK9, is significantly correlated with poor metastasis-free survival in a cohort of breast cancer patients. RNA sequencing revealed marked downregulation of pathways governing proliferation, transcription and cell survival in TNBC cells treated with the combination of an EGFR-TKI and a dual cdc7/CDK9 inhibitor. A number of genes enriched in these downregulated pathways are associated with poor metastasis-free survival in TNBC.

CONCLUSIONS

Our results highlight that dual inhibition of cdc7 and CDK9 by PHA-767491 is a potential strategy for targeting TNBC resistant to EGFR-TKIs.

Corrigendum: Investigation of Nrf2, AhR and ATF4 Activation in Toxicogenomic Databases

[This corrects the article DOI: 10.3389/fgene.2018.00429.].

Development of a neurotoxicity assay that is tuned to detect mitochondrial toxicants

Many neurotoxicants affect energy metabolism in man, but currently available test methods may still fail to predict mito- and neurotoxicity. We addressed this issue using LUHMES cells, i.e., human neuronal precursors that easily differentiate into mature neurons. Within the NeuriTox assay, they have been used to screen for neurotoxicants. Our new approach is based on culturing the cells in either glucose or galactose (Glc-Gal-NeuriTox) as the main carbohydrate source during toxicity testing. Using this Glc-Gal-NeuriTox assay, 52 mitochondrial and non-mitochondrial toxicants were tested. The panel of chemicals comprised 11 inhibitors of mitochondrial respiratory chain complex I (cI), 4 inhibitors of cII, 8 of cIII, and 2 of cIV; 8 toxicants were included as they are assumed to be mitochondrial uncouplers. In galactose, cells became more dependent on mitochondrial function, which made them 2-3 orders of magnitude more sensitive to various mitotoxicants. Moreover, galactose enhanced the specific neurotoxicity (destruction of neurites) compared to a general cytotoxicity (plasma membrane lysis) of the toxicants. The Glc-Gal-NeuriTox assay worked particularly well for inhibitors of cI and cIII, while the toxicity of uncouplers and non-mitochondrial toxicants did not differ significantly upon glucose ↔ galactose exchange. As a secondary assay, we developed a method to quantify the inhibition of all mitochondrial respiratory chain functions/complexes in LUHMES cells. The combination of the Glc-Gal-NeuriTox neurotoxicity screening assay with the mechanistic follow up of target site identification allowed both, a more sensitive detection of neurotoxicants and a sharper definition of the mode of action of mitochondrial toxicants.

System Microscopy of Stress Response Pathways in Cholestasis Research

Exposure to oxidative radical species and cytokine-mediated inflammatory stress are established contributors to hepatocyte cell death during cholestasis. Cellular counter measures against those stressors are called adaptive stress response pathways. While in early stages of the disease adaptive stress pathways protect the hepatocytes, in later stages during prolonged stressed conditions they fail. The quantitative imaging-based assessment of cellular stress response pathways using the HepG2 BAC-GFP response reporter platform is a powerful strategy to evaluate the impact of chemical substances and gene knockdown on activation of adaptive stress response pathways, hence allowing systematic screening for positive or negative influences on cholestasis progression. This protocol allows the application of a highly versatile screening tool for a systematic evaluation of the effect of compounds having cholestasis liability and affected genes during cholestatic injury on cellular adaptive stress pathway activation. The approach involves high-throughput live-cell visualization of GFP-tagged key proteins of the oxidative stress response/Nrf2 pathway and inflammatory cytokine signaling. Quantitative image analysis of temporal responses of individual cells is followed by informatics analysis. The overall practical approaches are discussed in this chapter.

Characterisation of the NRF2 transcriptional network and its response to chemical insult in primary human hepatocytes: implications for prediction of drug-induced liver injury

The transcription factor NRF2, governed by its repressor KEAP1, protects cells against oxidative stress. There is interest in modelling the NRF2 response to improve the prediction of clinical toxicities such as drug-induced liver injury (DILI). However, very little is known about the makeup of the NRF2 transcriptional network and its response to chemical perturbation in primary human hepatocytes (PHH), which are often used as a translational model for investigating DILI. Here, microarray analysis identified 108 transcripts (including several putative novel NRF2-regulated genes) that were both downregulated by siRNA targeting NRF2 and upregulated by siRNA targeting KEAP1 in PHH. Applying weighted gene co-expression network analysis (WGCNA) to transcriptomic data from the Open TG-GATES toxicogenomics repository (representing PHH exposed to 158 compounds) revealed four co-expressed gene sets or ‘modules’ enriched for these and other NRF2-associated genes. By classifying the 158 TG-GATES compounds based on published evidence, and employing the four modules as network perturbation metrics, we found that the activation of NRF2 is a very good indicator of the intrinsic biochemical reactivity of a compound (i.e. its propensity to cause direct chemical stress), with relatively high sensitivity, specificity, accuracy and positive/negative predictive values. We also found that NRF2 activation has lower sensitivity for the prediction of clinical DILI risk, although relatively high specificity and positive predictive values indicate that false positive detection rates are likely to be low in this setting. Underpinned by our comprehensive analysis, activation of the NRF2 network is one of several mechanism-based components that can be incorporated into holistic systems toxicology models to improve mechanistic understanding and preclinical prediction of DILI in man.

Current EU research activities on combined exposure to multiple chemicals

Humans and wildlife are exposed to an intractably large number of different combinations of chemicals via food, water, air, consumer products, and other media and sources. This raises concerns about their impact on public and environmental health. The risk assessment of chemicals for regulatory purposes mainly relies on the assessment of individual chemicals. If exposure to multiple chemicals is considered in a legislative framework, it is usually limited to chemicals falling within this framework and co-exposure to chemicals that are covered by a different regulatory framework is often neglected. Methodologies and guidance for assessing risks from combined exposure to multiple chemicals have been developed for different regulatory sectors, however, a harmonised, consistent approach for performing mixture risk assessments and management across different regulatory sectors is lacking. At the time of this publication, several EU research projects are running, funded by the current European Research and Innovation Programme Horizon 2020 or the Seventh Framework Programme. They aim at addressing knowledge gaps and developing methodologies to better assess chemical mixtures, by generating and making available internal and external exposure data, developing models for exposure assessment, developing tools for in silico and in vitro effect assessment to be applied in a tiered framework and for grouping of chemicals, as well as developing joint epidemiological-toxicological approaches for mixture risk assessment and for prioritising mixtures of concern. The projects EDC-MixRisk, EuroMix, EUToxRisk, HBM4EU and SOLUTIONS have started an exchange between the consortia, European Commission Services and EU Agencies, in order to identify where new methodologies have become available and where remaining gaps need to be further addressed. This paper maps how the different projects contribute to the data needs and assessment methodologies and identifies remaining challenges to be further addressed for the assessment of chemical mixtures.

Investigation of Nrf2, AhR and ATF4 Activation in Toxicogenomic Databases

Toxicological responses to chemical insult are largely regulated by transcriptionally activated pathways that may be independent, correlated and partially or fully overlapping. Investigating the dynamics of the interactions between stress responsive transcription factors from toxicogenomic data and defining the signature of each of them is an additional step toward a system level understanding of perturbation driven mechanisms. To this end, we investigated the segregation of the genes belonging to the three following transcriptionally regulated pathways: the AhR pathway, the Nrf2 pathway and the ATF4 pathway. Toxicogenomic datasets from three projects (carcinoGENOMICS, Predict-IV and TG-GATEs) obtained in various experimental conditions (in human and rat in vitro liver and kidney models and rat in vivo, with bolus administration and with repeated doses) were combined and consolidated where overlaps between datasets existed. A bioinformatic analysis was performed to refine pathways' signatures and to create chemical activation capacity scores to classify chemicals by their potency and selectivity of activation of each pathway. With some refinement such an approach may improve chemical safety classification and allow biological read across on a pathway level.

Comparison of base-line and chemical-induced transcriptomic responses in HepaRG and RPTEC/TERT1 cells using TempO-Seq

The utilisation of genome-wide transcriptomics has played a pivotal role in advancing the field of toxicology, allowing the mapping of transcriptional signatures to chemical exposures. These activities have uncovered several transcriptionally regulated pathways that can be utilised for assessing the perturbation impact of a chemical and also the identification of toxic mode of action. However, current transcriptomic platforms are not very amenable to high-throughput workflows due to, high cost, complexities in sample preparation and relatively complex bioinformatic analysis. Thus, transcriptomic investigations are usually limited in dose and time dimensions and are, therefore, not optimal for implementation in risk assessment workflows. In this study, we investigated a new cost-effective, transcriptomic assay, TempO-Seq, which alleviates the aforementioned limitations. This technique was evaluated in a 6-compound screen, utilising differentiated kidney (RPTEC/TERT1) and liver (HepaRG) cells and compared to non-transcriptomic label-free sensitive endpoints of chemical-induced disturbances, namely phase contrast morphology, xCELLigence and glycolysis. Non-proliferating cell monolayers were exposed to six sub-lethal concentrations of each compound for 24 h. The results show that utilising a 2839 gene panel, it is possible to discriminate basal tissue-specific signatures, generate dose-response relationships and to discriminate compound-specific and cell type-specific responses. This study also reiterates previous findings that chemical-induced transcriptomic alterations occur prior to cytotoxicity and that transcriptomics provides in depth mechanistic information of the effects of chemicals on cellular transcriptional responses. TempO-Seq is a robust transcriptomic platform that is well suited for in vitro toxicity experiments.

Abstract 1527: Splicing factors determine breast cancer cell mitosis through control of sister chromatid cohesion

Breast cancer is the mostly diagnosed cancer in women worldwide and is also the leading cause of death from cancer in women, mainly due to metastasis formation. Accumulating evidence suggests that RNA splicing is critical in breast cancer progression. To investigate the role of every single component of the splicing machinery (the spliceosome) in this process, we systematically evaluated the effect of siRNA-mediated knockdown of 244 splicing factors on proliferation in two highly proliferative breast cancer cell lines MDA-MB-231 and Hs578T. Hits of the primary screen were validated with single siRNAs and separated based on their effects on migration and proliferation respectively. Knockdown of nine validated proliferation hits, amongst which was SF3B1, a known breast cancer driver gene, resulted for all nine hits in a distinct poly-lobed nuclear phenotype in both cell types, accompanied by increased DNA content and higher number of cells in G1-S transition. Increased levels of phospho-Histone H3 and lack of metaphase alignment suggested a defect in mitosis, which was confirmed by decreased RNA expression of sister chromatid cohesion factors MAU2, ESPL1 and SMC1A and interestingly, increased CDCA5 RNA levels. Upon splicing factor knockdown, CDCA5 intron 1 was retained resulting in decreased CDCA5 protein levels, inaccurate metaphase alignment and finally cell death. To identify the direct partners of the splicing factors that control mitosis, we coupled pull-down of GFP fused splicing factors with mass spectrometry. Seven out of the nine splicing factors that were identified in our screen causing poly-lobed nuclear phenotypes, resided in the same protein complex together with proteins involved in snRNP assembly and some mitosis-related factors. In conclusion, we have identified several splicing factors that are critically determining breast cancer cell proliferation through modulating the expression of chromatid cohesion factors and thereby mediating the successful metaphase alignment and ultimate mitosis.

Citation Format: Esmee Koedoot, John Martens, Sylvia E. Le Dévédec, Bob van de Water. Splicing factors determine breast cancer cell mitosis through control of sister chromatid cohesion [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1527.

Abstract 5179: Uncovering the signaling landscape controlling breast cancer cell migration identifies splicing PRPF4B as a metastasis driver

Metastasis is the major cause of death in cancer patients and migration of cancer cells from the primary tumor to distant sites is the prerequisite of metastasis formation. Here we applied an imaging-based RNAi phenotypic cell migration screen uing two highly migratory basal breast cancer cell lines (Hs578T and MDA-MB-231 to provide a repository of candidate metastasis drug targets. We screened ~4,200 individual target genes covering most cell signaling components. We discovered 133 and 113 migratory modulators of Hs578T and MDA-MB-231, respectively, of which 45 genes were common denominators of cell migration. Interaction networks of candidate migratory modulators were in common with networks of different clinical breast cancer prognostic and metastasis classifiers. The splicing factors PRPF4B and BUD31 and the transcription factor BPTF were amplified in human primary breast tumors and the expression was associated with metastasis-free survival. Depletion of PRPF4B, BUD31 and BPTF caused primarily downregulation of genes involved in focal adhesion and ECM-interaction pathways. PRPF4B was essential for TNBC cell migration and critical for breast cancer metastasis formation in vivo, making PRPF4B a candidate for further drug development. Our systematic phenotypic screen provides an important repository for signaling determinants that functionally drive cancer cell migration.

Citation Format: Bob van de Water, Erik Danen, Esmee Koedoot, Maria Rogkoti, Michiel Fokkelman, Sylvia Le Devedec, John Martens, Peter Stoilov, John Foekens. Uncovering the signaling landscape controlling breast cancer cell migration identifies splicing PRPF4B as a metastasis driver [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5179.

Model-based identification of TNFα-induced IKKβ-mediated and IκBα-mediated regulation of NFκB signal transduction as a tool to quantify the impact of drug-induced liver injury compounds

Drug-induced liver injury (DILI) has become a major problem for patients and for clinicians, academics and the pharmaceutical industry. To date, existing hepatotoxicity test systems are only poorly predictive and the underlying mechanisms are still unclear. One of the factors known to amplify hepatotoxicity is the tumor necrosis factor alpha (TNFα), especially due to its synergy with commonly used drugs such as diclofenac. However, the exact mechanism of how diclofenac in combination with TNFα induces liver injury remains elusive. Here, we combined time-resolved immunoblotting and live-cell imaging data of HepG2 cells and primary human hepatocytes (PHH) with dynamic pathway modeling using ordinary differential equations (ODEs) to describe the complex structure of TNFα-induced NFκB signal transduction and integrated the perturbations of the pathway caused by diclofenac. The resulting mathematical model was used to systematically identify parameters affected by diclofenac. These analyses showed that more than one regulatory module of TNFα-induced NFκB signal transduction is affected by diclofenac, suggesting that hepatotoxicity is the integrated consequence of multiple changes in hepatocytes and that multiple factors define toxicity thresholds. Applying our mathematical modeling approach to other DILI-causing compounds representing different putative DILI mechanism classes enabled us to quantify their impact on pathway activation, highlighting the potential of the dynamic pathway model as a quantitative tool for the analysis of DILI compounds.

Glutathione S-Transferase P1 Protects Against Amodiaquine Quinoneimines-Induced Cytotoxicity but Does Not Prevent Activation of Endoplasmic Reticulum Stress in HepG2 Cells

Formation of the reactive amodiaquine quinoneimine (AQ-QI) and N-desethylamodiaquine quinoneimine (DEAQ-QI) plays an important role in the toxicity of the anti-malaria drug amodiaquine (AQ). Glutathione conjugation protects against AQ-induced toxicity and GSTP1 is able to conjugate its quinoneimine metabolites AQ-QI and DEA-QI with glutathione. In this study, HepG2 cells transiently transfected with the human GSTP1 construct were utilized to investigate the protective effect of GSTP1 in a cellular context. HepG2 cells were exposed to synthesized QIs, which bypasses the need for intracellular bioactivation of AQ or DEAQ. Exposure was accompanied by decreased cell viability, increased caspase 3 activity, and decreased intracellular GSH levels. Using high-content imaging-based BAC-GFP reporters, it was shown that AQ-QI and DEAQ-QI specifically activated the endoplasmic reticulum (ER) stress response. In contrast, oxidative stress, DNA damage, or inflammatory stress responses were not activated. Overexpression of GSTP1 resulted in a two-fold increase in GSH-conjugation of the QIs, attenuated QI-induced cytotoxicity especially under GSH-depletion condition, abolished QIs-induced apoptosis but did not significantly inhibit the activation of the ER stress response. In conclusion, these results indicate a protective role of GSTP1 by increasing enzymatic detoxification of AQ-QI and DEAQ-QI and suggest a second protective mechanism by interfering with ER stress induced apoptosis.

Abstract A023: Cell migration is a stronger predictor of patient survival in breast cancer than cell proliferation

Significance: The efficacy of anticancer drugs has been conventionally estimated in the laboratory by measuring post-treatment in vitro proliferation rates of cancer cell lines. The results of such in vitro measurements, however, rarely translate to human trials, thus posing a significant translational challenge. Additional cellular phenotypes have hence been studied in recent years, examining cell migration and invasion. Understanding how each of these in vitro measured phenotypes contributes to the patient response and survival is hence an important open challenge. Here, mining thousands of breast cancer tumors and cell-line experiments, we explore this relationship and delineate the individual contributions of these phenotypes, in predicting patient survival and response. Methods: Migration and proliferation was measured for 43 different breast cancer cell lines. Integrating these measurements with the cell lines' transcriptomics, we built gene expression-based predictors of each of these phenotypes in cell lines and in tumors. The predicted phenotypes were then used to study their contribution to patient survival. Results: Analyzing the transcriptomics of these cell lines, we identified specific gene-expression signatures of breast cancer migration and proliferation, that are highly predictive of these phenotypes (using cross validation). Subsequently, we applied these signatures to a collection of more than 2800 breast cancer tumors in the TCGA and METABRIC collection, to predict their proliferation and migration rates. Our analysis shows that both laboratory-measured proliferation and migration signatures are predictive of breast cancer stage, grade, subtypes, and finally, of patient survival. Notably, we find that the predicted migration rates of tumors are stronger predictors of patient survival than their predicted proliferation rates. This finding is further reinforced via analyzing migration and proliferation signatures that we derive from in vitro shRNA knockout experiments. We also find that patients whose tumors have high predicted migration rates specifically benefited from cytoskeletal drug treatments. Finally, we find that the predicted migration rates are associated with response of checkpoint inhibitor in patients. We are further extensively validating this by collecting tumor biopsies from patients post immunotherapy. Conclusions: Taken together, these results testify to the superiority of migration- over proliferation-based transcriptomic signatures in predicting breast cancer tumor phenotypes and patients’ survival. This suggests that in vitro migration measurements of drug response may significantly increase the translational value of cellular phenotypic measurements in predicting drug efficacy in patients. Finally, because tumor migration rates are predictive of cancer immunotherapy, they may provide a viable biomarker for immunotherapy response in patients.

Citation Format: Nishanth U. Nair, Avinash Das, Joo Sang Lee, Sridhar Hannenhalli, Sylvia Le Dévédec, Bob van de Water, Eytan Ruppin. Cell migration is a stronger predictor of patient survival in breast cancer than cell proliferation [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2017 Oct 26-30; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Ther 2018;17(1 Suppl):Abstract nr A023.

Abstract 893: Systematic assessment of spliceosome components as drivers of breast cancer progression

Accumulating evidence indicates that RNA splicing is involved in different steps of carcinogenesis. Although the critical role of a limited number of splicing factors has been demonstrated in several cancer studies, the function of many spliceosome components is still unknown. In breast cancer samples higher expression levels of a subset of spliceosome components consistently correlated with more aggressive tumor types in patient microarray as well as RNA sequencing data from The Cancer Genome Atlas (TCGA). We further systematically evaluated the effect of siRNA-mediated knockdown of 244 individual splicing factors on both cell migration and proliferation in two aggressive breast cancer cell lines MDA-MB-231 and Hs578T using high throughput microscopy. Primary candidates were validated with four single siRNAs and classified based on their effects on migration and proliferation. Knockdown of validated spliceosome factors such as SNRPG and SNRPA1 affected the levels of small nuclear RNAs, the main catalyzers of the spliceosome. Moreover, high expression of these key candidate hits is associated with poor breast cancer metastasis free survival. To investigate the downstream mechanisms and splicing patterns controlled by our candidate genes we performed RNA sequencing on both control and siRNA mediated knockdown cells. Interestingly, knockdown of our hits affect extracellular matrix pathways that are essential in tumor cell migration and invasion. Altogether our data indicate a key role for spliceosome factors in the control of breast cancer progression which provide new leads for future therapeutic intervention.

Citation Format: Esmee Koedoot, Sylvia Le Dévédec, Bob van de Water. Systematic assessment of spliceosome components as drivers of breast cancer progression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 893. doi:10.1158/1538-7445.AM2017-893

Abstract 103: Blockage of Cdc7/CDK9 signaling sensitizes triple negative breast cancer to EGFR-targeted therapy

The treatment of Triple-Negative Breast Cancer (TNBC) still represents a profound clinical challenge, the disease being disproportionately responsible for breast cancer-associated deaths. As a consequence, the identification of targeted agents, which synergize with current therapeutic options, is paramount. Resistance to EGFR-tyrosine kinase inhibitors (TKIs), despite frequent EGFR overexpression and reliance on downstream signalling pathways in TNBC, remains endemic. Recent data has also suggested that kinase-inhibition of EGFR in itself is insufficient, given the kinase-independent functions of the protein in transcriptional regulation and DNA-repair may permit prolonged EGFR-mediated signalling in the presence of inhibitors. We performed a kinase inhibitor drug screen (378 kinase inhibitors targeting ~40 different cancer-related kinases) to identify synergistic activity with EGFR inhibition in TNBC. We demonstrate that the dual cdc7/CDK9 inhibitor PHA-767491 synergizes with multiple EGFR-TKIs (Erlotinib, Gefitinib and Lapatinib) in vitro to overcome resistance to EGFR-targeted therapy in various TNBC cell lines. Combined inhibition of EGFR and cdc7/CDK9 resulted in reduced cell proliferation, accompanied by induction of apoptosis and G2-M cell cycle-arrest. Combination therapy inhibited crucial components of the DNA-replicative machinery and also proteins involved in CDK9-mediated transcriptional elongation. Moreover, higher expression of cdc7 and POLR2A was found to be significantly correlated with poorer survival rates in breast cancer patients. Additionally, this synergistic combination effectively inhibited the growth of cells isolated from patient-derived TNBC xenografts under ex vivo culture conditions, highlighting the utility of targeting common transcriptional nodes in cancers addicted to growth factor-mediated signalling pathways.

Citation Format: Ronan P. McLaughlin, Jichao He, Vera van der Noord, Jevin Redel, Marcel Smid, Lambert Dorssers, John Martens, John Foekens, Yinghui Zhang, Bob van de Water. Blockage of Cdc7/CDK9 signaling sensitizes triple negative breast cancer to EGFR-targeted therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 103. doi:10.1158/1538-7445.AM2017-103

High-Throughput Phenotypic Screening of Kinase Inhibitors to Identify Drug Targets for Polycystic Kidney Disease

Polycystic kidney disease (PKD) is a prevalent disorder characterized by renal cysts that lead to kidney failure. Various signaling pathways have been targeted to stop disease progression, but most interventions still focus on alleviating PKD-associated symptoms. The mechanistic complexity of the disease, as well as the lack of functional in vitro assays for compound testing, has made drug discovery for PKD challenging. To identify modulators of PKD, Pkd1^–/– kidney tubule epithelial cells were applied to a scalable and automated 3D cyst culture model for compound screening, followed by phenotypic profiling to determine compound efficacy. We used this screening platform to screen a library of 273 kinase inhibitors to probe various signaling pathways involved in cyst growth. We show that inhibition of several targets, including aurora kinase, CDK, Chk, IGF-1R, Syk, and mTOR, but, surprisingly, not PI3K, prevented forskolin-induced cyst swelling. Additionally, we show that multiparametric phenotypic classification discriminated potentially undesirable (i.e., cytotoxic) compounds from molecules inducing the desired phenotypic change, greatly facilitating hit selection and validation. Our findings show that a pathophysiologically relevant 3D cyst culture model of PKD coupled to phenotypic profiling can be used to identify potentially therapeutic compounds and predict and validate molecular targets for PKD.

Insulin-like growth factor 1 receptor activation promotes mammary gland tumor development by increasing glycolysis and promoting biomass production

Background

The insulin-like growth factor 1 (IGF1) signaling axis plays a major role in tumorigenesis. In a previous experiment, we chronically treated mice with several agonists of the IGF1 receptor (IGF1R). We found that chronic treatment with insulin analogues with high affinity towards the IGF1R (IGF1 and X10) decreased the mammary gland tumor latency time in a p53^R270H/+WAPCre mouse model. Frequent injections with insulin analogues that only mildly activated the IGF1R in vivo (glargine and insulin) did not significantly decrease the tumor latency time in this mouse model.

Methods

Here, we performed next-generation RNA sequencing (40 million, 100 bp reads) on 50 mammary gland tumors to unravel the underlying mechanisms of IGF1R-promoted tumorigenesis. Mutational profiling of the individual tumors was performed to screen for treatment-specific mutations. The transcriptomic data were used to construct a support vector machine (SVM) classifier so that the phenotypic characteristics of tumors exposed to the different insulin analogue treatments could be predicted. For translational purposes, we ran the same classifiers on transcriptomic (micro-array) data of insulin analogue-exposed human breast cancer cell lines. Genome-scale metabolic modeling was performed with iMAT.

Results

We found that chronic X10 and IGF1 treatment resulted in tumors with an increased and sustained proliferative and invasive transcriptomic profile. Furthermore, a Warburg-like effect with increased glycolysis was observed in tumors of the X10/IGF1 groups and, to a lesser extent, also in glargine-induced tumors. A metabolic flux analysis revealed that this enhanced glycolysis programming in X10/IGF1 tumors was associated with increased biomass production programs. Although none of the treatments induced genetic instability or enhanced mutagenesis, mutations in Ezh2 and Hras were enriched in X10/IGF1 treatment tumors.

Conclusions

Overall, these data suggest that the decreased mammary gland tumor latency time caused by chronic IGF1R activation is related to modulation of tumor progression rather than increased tumor initiation.

Electronic supplementary material

The online version of this article (doi:10.1186/s13058-017-0802-0) contains supplementary material, which is available to authorized users.

Stem cell-derived models to improve mechanistic understanding and prediction of human drug-induced liver injury

Current preclinical drug testing does not predict some forms of adverse drug reactions in humans. Efforts at improving predictability of drug-induced tissue injury in humans include using stem cell technology to generate human cells for screening for adverse effects of drugs in humans. The advent of induced pluripotent stem cells means that it may ultimately be possible to develop personalized toxicology to determine interindividual susceptibility to adverse drug reactions. However, the complexity of idiosyncratic drug-induced liver injury means that no current single-cell model, whether of primary liver tissue origin, from liver cell lines, or derived from stem cells, adequately emulates what is believed to occur during human drug-induced liver injury. Nevertheless, a single-cell model of a human hepatocyte which emulates key features of a hepatocyte is likely to be valuable in assessing potential chemical risk; furthermore, understanding how to generate a relevant hepatocyte will also be critical to efforts to build complex multicellular models of the liver. Currently, hepatocyte-like cells differentiated from stem cells still fall short of recapitulating the full mature hepatocellular phenotype. Therefore, we convened a number of experts from the areas of preclinical and clinical hepatotoxicity and safety assessment, from industry, academia, and regulatory bodies, to specifically explore the application of stem cells in hepatotoxicity safety assessment and to make recommendations for the way forward. In this short review, we particularly discuss the importance of benchmarking stem cell-derived hepatocyte-like cells to their terminally differentiated human counterparts using defined phenotyping, to make sure the cells are relevant and comparable between labs, and outline why this process is essential before the cells are introduced into chemical safety assessment. (Hepatology 2017;65:710-721).

Comprehensive Landscape of Nrf2 and p53 Pathway Activation Dynamics by Oxidative Stress and DNA Damage

A quantitative dynamics pathway map of the Nrf2-mediated oxidative stress response and p53-related DNA damage response pathways as well as the cross-talk between these pathways has not systematically been defined. To allow the dynamic single cell evaluation of these pathways, we have used BAC-GFP recombineering to tag for each pathway's three key components: for the oxidative stress response, Keap1-GFP, Nrf2-GFP, and Srxn1-GFP; for the DNA damage response, 53bp1-GFP, p53-GFP, and p21-GFP. The dynamic activation of these individual components was assessed using quantitative high throughput confocal microscopy after treatment with a broad concentration range of diethyl maleate (DEM; to induce oxidative stress) and etoposide (to induce DNA damage). DEM caused a rapid activation of Nrf2, which returned to baseline levels at low concentrations but remained sustained at high concentrations. Srxn1-GFP induction and Keap1-GFP translocation to autophagosomes followed later, with upper boundaries reached at high concentrations, close to the onset of cell death. Etoposide caused rapid accumulation of 53bp1-GFP in DNA damage foci, which was later followed by the concentration dependent nuclear accumulation of p53-GFP and subsequent induction of p21-GFP. While etoposide caused activation of Srxn1-GFP, a modest activation of DNA damage reporters was observed for DEM at high concentrations. Interestingly, Nrf2 knockdown caused an inhibition of the DNA damage response at high concentrations of etoposide, while Keap1 knockdown caused an enhancement of the DNA damage response already at low concentrations of etoposide. Knockdown of p53 did not affect the oxidative stress response. Altogether, the current stress response landscapes provide insight in the time course responses of and cross-talk between oxidative stress and DNA-damage and defines the tipping points where cell injury may switch from adaptation to injury.