Uncovering the Signaling Landscape Controlling Breast Cancer Cell Migration Identifies Novel Metastasis Driver Genes

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 developmen

Uncovering the signaling landscape controlling breast cancer cell migration identifies novel metastasis driver genes

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

Alternative signaling network activation through different insulin receptor family members caused by pro-mitogenic antidiabetic insulin analogues in human mammary epithelial cells

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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13058-015-0600-5) contains supplementary material, which is available to authorized users

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

Organoids as a biomarker for personalized treatment in metastatic colorectal cancer: drug screen optimization and correlation with patient response

Abstract Background The inability to predict treatment response of colorectal cancer patients results in unnecessary toxicity, decreased efficacy and survival. Response testing on patient-derived organoids (PDOs) is a promising biomarker for treatment efficacy. The aim of this study is to optimize PDO drug screening methods for correlation with patient response and explore the potential to predict responses to standard chemotherapies. Methods We optimized drug screen methods on 5–11 PDOs per condition of the complete set of 23 PDOs from patients treated for metastatic colorectal cancer (mCRC). PDOs were exposed to 5-fluorouracil (5-FU), irinotecan- and oxaliplatin-based chemotherapy. We compared medium with and without N-acetylcysteine (NAC), different readouts and different combination treatment set-ups to capture the strongest association with patient response. We expanded the screens using the optimized methods for all PDOs. Organoid sensitivity was correlated to the patient’s response, determined by % change in the size of target lesions. We assessed organoid sensitivity in relation to prior exposure to chemotherapy, mutational status and sidedness. Results Drug screen optimization involved excluding N-acetylcysteine from the medium and biphasic curve fitting for 5-FU & oxaliplatin combination screens. CellTiter-Glo measurements were comparable with CyQUANT and did not affect the correlation with patient response. Furthermore, the correlation improved with application of growth rate metrics, when 5-FU & oxaliplatin was screened in a ratio, and 5-FU & SN-38 using a fixed dose of SN-38. Area under the curve was the most robust drug response curve metric. After optimization, organoid and patient response showed a correlation coefficient of 0.58 for 5-FU (n = 6, 95% CI -0.44,0.95), 0.61 for irinotecan- (n = 10, 95% CI -0.03,0.90) and 0.60 for oxaliplatin-based chemotherapy (n = 11, 95% CI -0.01,0.88). Median progression-free survival of patients with resistant PDOs to oxaliplatin-based chemotherapy was significantly shorter than sensitive PDOs (3.3 vs 10.9 months, p = 0.007). Increased resistance to 5-FU in patients with prior exposure to 5-FU/capecitabine was adequately reflected in PDOs (p = 0.003). Conclusions Our study emphasizes the critical impact of the screening methods for determining correlation between PDO drug screens and mCRC patient outcomes. Our 5-step optimization strategy provides a basis for future research on the clinical utility of PDO screens

Additional file 1 of Organoids as a biomarker for personalized treatment in metastatic colorectal cancer: drug screen optimization and correlation with patient response

Additional file 1: Supplementary Table 1. Composition of organoid culture medium. Supplementary Table 2. Chemotherapies and targeted treatments used in drug screens. Supplementary Table 3. Baseline characteristics of the cohort of patients. Supplementary Table 4. Quality control analysis of the drug screens showing the Z’-factor. Supplementary Fig. 1. Quality control analysis of the drug screens illustrating the difference between duplicate assays. Supplementary Fig. 2. Individual drug response curves for each PDO per treatment. Supplementary Fig. 3. Comparing different drug screening methods. Supplementary Fig. 4. The impact of different drug screening methods on organoid sensitivity and correlation with patient response