Phosphorylation of AIB1 at Mitosis Is Regulated by CDK1/CYCLIN B

Although the AIB1 oncogene has an important role during the early phase of the cell cycle as a coactivator of E2F1, little is known about its function during mitosis.Mitotic cells isolated by nocodazole treatment as well as by shake-off revealed a post-translational modification occurring in AIB1 specifically during mitosis. This modification was sensitive to the treatment with phosphatase, suggesting its modification by phosphorylation. Using specific inhibitors and in vitro kinase assays we demonstrate that AIB1 is phosphorylated on Ser728 and Ser867 by Cdk1/cyclin B at the onset of mitosis and remains phosphorylated until exit from M phase. Differences in the sensitivity to phosphatase inhibitors suggest that PP1 mediates dephosphorylation of AIB1 at the end of mitosis. The phosphorylation of AIB1 during mitosis was not associated with ubiquitylation or degradation, as confirmed by western blotting and flow cytometry analysis. In addition, luciferase reporter assays showed that this phosphorylation did not alter the transcriptional properties of AIB1. Importantly, fluorescence microscopy and sub-cellular fractionation showed that AIB1 phosphorylation correlated with the exclusion from the condensed chromatin, thus preventing access to the promoters of AIB1-dependent genes. Phospho-specific antibodies developed against Ser728 further demonstrated the presence of phosphorylated AIB1 only in mitotic cells where it was localized preferentially in the periphery of the cell.Collectively, our results describe a new mechanism for the regulation of AIB1 during mitosis, whereby phosphorylation of AIB1 by Cdk1 correlates with the subcellular redistribution of AIB1 from a chromatin-associated state in interphase to a more peripheral localization during mitosis. At the exit of mitosis, AIB1 is dephosphorylated, presumably by PP1. This exclusion from chromatin during mitosis may represent a mechanism for governing the transcriptional activity of AIB1

Exosomal microRNAs from Longitudinal Liquid Biopsies for the Prediction of Response to Induction Chemotherapy in High-Risk Neuroblastoma Patients: A Proof of Concept SIOPEN Study

Despite intensive treatment, 50% of children with high-risk neuroblastoma (HR-NB) succumb to their disease. Progression through current trials evaluating the efficacy of new treatments for children with HR disease usually depends on an inadequate response to induction chemotherapy, assessed using imaging modalities. In this study, we sought to identify circulating biomarkers that might be detected in a simple blood sample to predict patient response to induction chemotherapy. Since exosomes released by tumor cells can drive tumor growth and chemoresistance, we tested the hypothesis that exosomal microRNA (exo-miRNAs) in blood might predict response to induction chemotherapy. The exo-miRNAs expression profile in plasma samples collected from children treated in HR-NBL-1/SIOPEN before and after induction chemotherapy was compared to identify a three exo-miRs signature that could discriminate between poor and good responders. Exo-miRNAs expression also provided a chemoresistance index predicting the good or poor prognosis of HR-NB patients

Frequency and Prognostic Impact of ALK Amplifications and Mutations in the European Neuroblastoma Study Group (SIOPEN) High-Risk Neuroblastoma Trial (HR-NBL1).

In neuroblastoma (NB), the ALK receptor tyrosine kinase can be constitutively activated through activating point mutations or genomic amplification. We studied ALK genetic alterations in high-risk (HR) patients on the HR-NBL1/SIOPEN trial to determine their frequency, correlation with clinical parameters, and prognostic impact. Diagnostic tumor samples were available from 1,092 HR-NBL1/SIOPEN patients to determine ALK amplification status (n = 330), ALK mutational profile (n = 191), or both (n = 571). Genomic ALK amplification (ALKa) was detected in 4.5% of cases (41 out of 901), all except one with MYCN amplification (MNA). ALKa was associated with a significantly poorer overall survival (OS) (5-year OS: ALKa [n = 41] 28% [95% CI, 15 to 42]; no-ALKa [n = 860] 51% [95% CI, 47 to 54], [P < .001]), particularly in cases with metastatic disease. ALK mutations (ALKm) were detected at a clonal level (> 20% mutated allele fraction) in 10% of cases (76 out of 762) and at a subclonal level (mutated allele fraction 0.1%-20%) in 3.9% of patients (30 out of 762), with a strong correlation between the presence of ALKm and MNA (P < .001). Among 571 cases with known ALKa and ALKm status, a statistically significant difference in OS was observed between cases with ALKa or clonal ALKm versus subclonal ALKm or no ALK alterations (5-year OS: ALKa [n = 19], 26% [95% CI, 10 to 47], clonal ALKm [n = 65] 33% [95% CI, 21 to 44], subclonal ALKm (n = 22) 48% [95% CI, 26 to 67], and no alteration [n = 465], 51% [95% CI, 46 to 55], respectively; P = .001). Importantly, in a multivariate model, involvement of more than one metastatic compartment (hazard ratio [HR], 2.87; P < .001), ALKa (HR, 2.38; P = .004), and clonal ALKm (HR, 1.77; P = .001) were independent predictors of poor outcome. Genetic alterations of ALK (clonal mutations and amplifications) in HR-NB are independent predictors of poorer survival. These data provide a rationale for integration of ALK inhibitors in upfront treatment of HR-NB with ALK alterations

A Genomic Approach for the Identification and Classification of Genes Involved in Cell Wall Formation and its Regulation in Saccharomyces Cerevisiae

Using a hierarchical approach, 620 non-essential single-gene yeast deletants generated by EUROFAN I were systematically screened for cell-wall-related phenotypes. By analyzing for altered sensitivity to the presence of Calcofluor white or SDS in the growth medium, altered sensitivity to sonication, or abnormal morphology, 145 (23%) mutants showing at least one cell wall-related phenotype were selected. These were screened further to identify genes potentially involved in either the biosynthesis, remodeling or coupling of cell wall macromolecules or genes involved in the overall regulation of cell wall construction and to eliminate those genes with a more general, pleiotropic effect. Ninety percent of the mutants selected from the primary tests showed additional cell wall-related phenotypes. When extrapolated to the entire yeast genome, these data indicate that over 1200 genes may directly or indirectly affect cell wall formation and its regulation. Twenty-one mutants with altered levels of β1,3-glucan synthase activity and five Calcofluor white-resistant mutants with altered levels of chitin synthase activities were found, indicating that the corresponding genes affect β1,3-glucan or chitin synthesis. By selecting for increased levels of specific cell wall components in the growth medium, we identified 13 genes that are possibly implicated in different steps of cell wall assembly. Furthermore, 14 mutants showed a constitutive activation of the cell wall integrity pathway, suggesting that they participate in the modulation of the pathway either directly acting as signaling components or by triggering the Slt2-dependent compensatory mechanism. In conclusion, our screening approach represents a comprehensive functional analysis on a genomic scale of gene products involved in various aspects of fungal cell wall formation

Robust association between vascular habitats and patient prognosis in glioblastoma: an international retrospective multicenter study

This is the peer reviewed version of the following article: del Mar Álvarez-Torres, M., Juan-Albarracín, J., Fuster-Garcia, E., Bellvís-Bataller, F., Lorente, D., Reynés, G., Font de Mora, J., Aparici-Robles, F., Botella, C., Muñoz-Langa, J., Faubel, R., Asensio-Cuesta, S., García-Ferrando, G.A., Chelebian, E., Auger, C., Pineda, J., Rovira, A., Oleaga, L., Mollà-Olmos, E., Revert, A.J., Tshibanda, L., Crisi, G., Emblem, K.E., Martin, D., Due-Tønnessen, P., Meling, T.R., Filice, S., Sáez, C. and García-Gómez, J.M. (2020), Robust association between vascular habitats and patient prognosis in glioblastoma: An international multicenter study. J Magn Reson Imaging, 51: 1478-1486, which has been published in final form at https://doi.org/10.1002/jmri.26958. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.[EN] Background Glioblastoma (GBM) is the most aggressive primary brain tumor, characterized by a heterogeneous and abnormal vascularity. Subtypes of vascular habitats within the tumor and edema can be distinguished: high angiogenic tumor (HAT), low angiogenic tumor (LAT), infiltrated peripheral edema (IPE), and vasogenic peripheral edema (VPE). Purpose To validate the association between hemodynamic markers from vascular habitats and overall survival (OS) in glioblastoma patients, considering the intercenter variability of acquisition protocols. Study Type Multicenter retrospective study. Population In all, 184 glioblastoma patients from seven European centers participating in the NCT03439332 clinical study. Field Strength/Sequence 1.5T (for 54 patients) or 3.0T (for 130 patients). Pregadolinium and postgadolinium-based contrast agent-enhanced T-1-weighted MRI, T-2- and FLAIR T-2-weighted, and dynamic susceptibility contrast (DSC) T-2* perfusion. Assessment We analyzed preoperative MRIs to establish the association between the maximum relative cerebral blood volume (rCBV(max)) at each habitat with OS. Moreover, the stratification capabilities of the markers to divide patients into "vascular" groups were tested. The variability in the markers between individual centers was also assessed. Statistical Tests Uniparametric Cox regression; Kaplan-Meier test; Mann-Whitney test. Results The rCBV(max) derived from the HAT, LAT, and IPE habitats were significantly associated with patient OS (P < 0.05; hazard ratio [HR]: 1.05, 1.11, 1.28, respectively). Moreover, these markers can stratify patients into "moderate-" and "high-vascular" groups (P < 0.05). The Mann-Whitney test did not find significant differences among most of the centers in markers (HAT: P = 0.02-0.685; LAT: P = 0.010-0.769; IPE: P = 0.093-0.939; VPE: P = 0.016-1.000). Data Conclusion The rCBV(max) calculated in HAT, LAT, and IPE habitats have been validated as clinically relevant prognostic biomarkers for glioblastoma patients in the pretreatment stage. This study demonstrates the robustness of the hemodynamic tissue signature (HTS) habitats to assess the GBM vascular heterogeneity and their association with patient prognosis independently of intercenter variability. Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019.This work was partially supported by: MTS4up project (National Plan for Scientific and Technical Research and Innovation 2013-2016, No. DPI2016-80054-R) (to J.M.G.G.); H2020-SC1-2016-CNECT Project (No. 727560) (to J.M.G.G.) and H2020-SC1-BHC-2018-2020 (No. 825750) (to J.M.G.G.); M.A.T was supported by DPI2016-80054-R (Programa Estatal de Promocion del Talento y su Empleabilidad en I + D + i). The data acquisition and curation of the Oslo University Hospital was supported by: the European Research Council (ERC) under the European Union's Horizon 2020 (Grant Agreement No. 758657), the South-Eastern Norway Regional Health Authority Grants 2017073 and 2013069, and the Research Council of Norway Grants 261984 (to K.E.E.). We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan V GPU used for this research. E.F.G. was supported by the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 844646. Figure 1 was designed by the Science Artist Elena Poritskaya.Álvarez-Torres, MDM.; Juan-Albarracín, J.; Fuster García, E.; Bellvís-Bataller, F.; Lorente, D.; Reynés, G.; Font De Mora, J.... (2020). Robust association between vascular habitats and patient prognosis in glioblastoma: an international retrospective multicenter study. Journal of Magnetic Resonance Imaging. 51(5):1478-1486. https://doi.org/10.1002/jmri.2695814781486515Louis, D. N., Perry, A., Reifenberger, G., von Deimling, A., Figarella-Branger, D., Cavenee, W. K., … Ellison, D. W. (2016). The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary. Acta Neuropathologica, 131(6), 803-820. doi:10.1007/s00401-016-1545-1Gately, L., McLachlan, S., Dowling, A., & Philip, J. (2017). Life beyond a diagnosis of glioblastoma: a systematic review of the literature. Journal of Cancer Survivorship, 11(4), 447-452. doi:10.1007/s11764-017-0602-7Bae, S., Choi, Y. S., Ahn, S. S., Chang, J. H., Kang, S.-G., Kim, E. H., … Lee, S.-K. (2018). Radiomic MRI Phenotyping of Glioblastoma: Improving Survival Prediction. Radiology, 289(3), 797-806. doi:10.1148/radiol.2018180200Akbari, H., Macyszyn, L., Da, X., Wolf, R. L., Bilello, M., Verma, R., … Davatzikos, C. (2014). Pattern Analysis of Dynamic Susceptibility Contrast-enhanced MR Imaging Demonstrates Peritumoral Tissue Heterogeneity. Radiology, 273(2), 502-510. doi:10.1148/radiol.14132458Weis, S. M., & Cheresh, D. A. (2011). Tumor angiogenesis: molecular pathways and therapeutic targets. Nature Medicine, 17(11), 1359-1370. doi:10.1038/nm.2537De Palma, M., Biziato, D., & Petrova, T. V. (2017). Microenvironmental regulation of tumour angiogenesis. Nature Reviews Cancer, 17(8), 457-474. doi:10.1038/nrc.2017.51Jain, R., Poisson, L. M., Gutman, D., Scarpace, L., Hwang, S. N., Holder, C. A., … Flanders, A. (2014). Outcome Prediction in Patients with Glioblastoma by Using Imaging, Clinical, and Genomic Biomarkers: Focus on the Nonenhancing Component of the Tumor. Radiology, 272(2), 484-493. doi:10.1148/radiol.14131691Jensen, R. L., Mumert, M. L., Gillespie, D. L., Kinney, A. Y., Schabel, M. C., & Salzman, K. L. (2013). Preoperative dynamic contrast-enhanced MRI correlates with molecular markers of hypoxia and vascularity in specific areas of intratumoral microenvironment and is predictive of patient outcome. Neuro-Oncology, 16(2), 280-291. doi:10.1093/neuonc/not148Jena, A., Taneja, S., Gambhir, A., Mishra, A. K., D’souza, M. M., Verma, S. M., … Sogani, S. K. (2016). Glioma Recurrence Versus Radiation Necrosis. Clinical Nuclear Medicine, 41(5), e228-e236. doi:10.1097/rlu.0000000000001152Price, S. J., Young, A. M. H., Scotton, W. J., Ching, J., Mohsen, L. A., Boonzaier, N. R., … Larkin, T. J. (2015). Multimodal MRI can identify perfusion and metabolic changes in the invasive margin of glioblastomas. Journal of Magnetic Resonance Imaging, 43(2), 487-494. doi:10.1002/jmri.24996Chang, Y.-C. C., Ackerstaff, E., Tschudi, Y., Jimenez, B., Foltz, W., Fisher, C., … Stoyanova, R. (2017). Delineation of Tumor Habitats based on Dynamic Contrast Enhanced MRI. Scientific Reports, 7(1). doi:10.1038/s41598-017-09932-5Cui, Y., Tha, K. K., Terasaka, S., Yamaguchi, S., Wang, J., Kudo, K., … Li, R. (2016). Prognostic Imaging Biomarkers in Glioblastoma: Development and Independent Validation on the Basis of Multiregion and Quantitative Analysis of MR Images. Radiology, 278(2), 546-553. doi:10.1148/radiol.2015150358Juan-Albarracín, J., Fuster-Garcia, E., Pérez-Girbés, A., Aparici-Robles, F., Alberich-Bayarri, Á., Revert-Ventura, A., … García-Gómez, J. M. (2018). Glioblastoma: Vascular Habitats Detected at Preoperative Dynamic Susceptibility-weighted Contrast-enhanced Perfusion MR Imaging Predict Survival. Radiology, 287(3), 944-954. doi:10.1148/radiol.2017170845Fuster-Garcia, E., Juan-Albarracín, J., García-Ferrando, G. A., Martí-Bonmatí, L., Aparici-Robles, F., & García-Gómez, J. M. (2018). Improving the estimation of prognosis for glioblastoma patients by MR based hemodynamic tissue signatures. NMR in Biomedicine, 31(12), e4006. doi:10.1002/nbm.4006Abramson, R. G., Burton, K. R., Yu, J.-P. J., Scalzetti, E. M., Yankeelov, T. E., Rosenkrantz, A. B., … Subramaniam, R. M. (2015). Methods and Challenges in Quantitative Imaging Biomarker Development. Academic Radiology, 22(1), 25-32. doi:10.1016/j.acra.2014.09.001Stupp, R., Mason, W. P., van den Bent, M. J., Weller, M., Fisher, B., Taphoorn, M. J. B., … Mirimanoff, R. O. (2005). Radiotherapy plus Concomitant and Adjuvant Temozolomide for Glioblastoma. New England Journal of Medicine, 352(10), 987-996. doi:10.1056/nejmoa043330Wetzel, S. G., Cha, S., Johnson, G., Lee, P., Law, M., Kasow, D. L., … Xue, X. (2002). Relative Cerebral Blood Volume Measurements in Intracranial Mass Lesions: Interobserver and Intraobserver Reproducibility Study. Radiology, 224(3), 797-803. doi:10.1148/radiol.2243011014Schnack, H. G., van Haren, N. E. M., Hulshoff Pol, H. E., Picchioni, M., Weisbrod, M., Sauer, H., … Kahn, R. S. (2004). Reliability of brain volumes from multicenter MRI acquisition: A calibration study. Human Brain Mapping, 22(4), 312-320. doi:10.1002/hbm.20040De Guio, F., Jouvent, E., Biessels, G. J., Black, S. E., Brayne, C., Chen, C., … Chabriat, H. (2016). Reproducibility and variability of quantitative magnetic resonance imaging markers in cerebral small vessel disease. Journal of Cerebral Blood Flow & Metabolism, 36(8), 1319-1337. doi:10.1177/0271678x16647396Hirai, T., Murakami, R., Nakamura, H., Kitajima, M., Fukuoka, H., Sasao, A., … Yamashita, Y. (2008). Prognostic Value of Perfusion MR Imaging of High-Grade Astrocytomas: Long-Term Follow-Up Study. American Journal of Neuroradiology, 29(8), 1505-1510. doi:10.3174/ajnr.a1121Sawlani, R. N., Raizer, J., Horowitz, S. W., Shin, W., Grimm, S. A., Chandler, J. P., … Carroll, T. J. (2010). Glioblastoma: A Method for Predicting Response to Antiangiogenic Chemotherapy by Using MR Perfusion Imaging—Pilot Study. Radiology, 255(2), 622-628. doi:10.1148/radiol.10091341Hambardzumyan, D., & Bergers, G. (2015). Glioblastoma: Defining Tumor Niches. Trends in Cancer, 1(4), 252-265. doi:10.1016/j.trecan.2015.10.009Artzi, M., Bokstein, F., Blumenthal, D. T., Aizenstein, O., Liberman, G., Corn, B. W., & Ben Bashat, D. (2014). Differentiation between vasogenic-edema versus tumor-infiltrative area in patients with glioblastoma during bevacizumab therapy: A longitudinal MRI study. European Journal of Radiology, 83(7), 1250-1256. doi:10.1016/j.ejrad.2014.03.02

Biomarkers characterization of circulating tumour cells in breast cancer patients

Introduction: Increasing evidence supports the view that the detection of circulating tumor cells (CTCs) predicts outcomes of nonmetastatic breast cancer patients. CTCs differ genetically from the primary tumor and may contribute to variations in prognosis and response to therapy. As we start to understand more about the biology of CTCs, we can begin to address how best to treat this form of disease. Methods: Ninety-eight nonmetastatic breast cancer patients were included in this study. CTCs were isolated by immunomagnetic techniques using magnetic beads labelled with a multi-CK-specific antibody (CK3-11D5) and CTC detection through immunocytochemical methods. Estrogen receptor, progesterone receptor and epidermal growth factor receptor (EGFR) were evaluated by immunofluorescence experiments and HER2 and TOP2A by fluorescence in situ hybridization. We aimed to characterize this set of biomarkers in CTCs and correlate it with clinical-pathological characteristics. Results: Baseline detection rate was 46.9% ≥ 1 CTC/30 ml threshold. CTC-positive cells were more frequent in HER2-negative tumors (p = 0.046). In patients younger than 50 years old, HER2-amplified and G1-G2 tumors had a higher possibility of being nondetectable CTCs. Heterogeneous expression of hormonal receptors (HRs) in samples from the same patients was found. Discordances between HR expression, HER2 and TOP2A status in CTCs and their primary tumor were found in the sequential blood samples. Less that 35% of patients switched their CTC status after receiving chemotherapy. EGFR-positive CTCs were associated with Luminal tumors (p = 0.03). Conclusions: This is the largest exploratory CTC biomarker analysis in nonmetastatic BC patients. Our study suggests that CTC biomarkers profiles might be useful as a surrogate marker for therapeutic selection and monitoring since heterogeneity of the biomarker distribution in CTCs and the lack of correlation with the primary tumor biomarker status were found. Further exploration of the association between EGFR-positive CTCs and Luminal tumors is warranted

Genomics of Signaling Crosstalk of Estrogen Receptor α in Breast Cancer Cells

BACKGROUND: The estrogen receptor alpha (ERalpha) is a ligand-regulated transcription factor. However, a wide variety of other extracellular signals can activate ERalpha in the absence of estrogen. The impact of these alternate modes of activation on gene expression profiles has not been characterized. METHODOLOGY/PRINCIPAL FINDINGS: We show that estrogen, growth factors and cAMP elicit surprisingly distinct ERalpha-dependent transcriptional responses in human MCF7 breast cancer cells. In response to growth factors and cAMP, ERalpha primarily activates and represses genes, respectively. The combined treatments with the anti-estrogen tamoxifen and cAMP or growth factors regulate yet other sets of genes. In many cases, tamoxifen is perverted to an agonist, potentially mimicking what is happening in certain tamoxifen-resistant breast tumors and emphasizing the importance of the cellular signaling environment. Using a computational analysis, we predicted that a Hox protein might be involved in mediating such combinatorial effects, and then confirmed it experimentally. Although both tamoxifen and cAMP block the proliferation of MCF7 cells, their combined application stimulates it, and this can be blocked with a dominant-negative Hox mutant. CONCLUSIONS/SIGNIFICANCE: The activating signal dictates both target gene selection and regulation by ERalpha, and this has consequences on global gene expression patterns that may be relevant to understanding the progression of ERalpha-dependent carcinomas

Proteomic Analysis of Pathways Involved in Estrogen-Induced Growth and Apoptosis of Breast Cancer Cells

Estrogen is a known growth promoter for estrogen receptor (ER)-positive breast cancer cells. Paradoxically, in breast cancer cells that have been chronically deprived of estrogen stimulation, re-introduction of the hormone can induce apoptosis.Here, we sought to identify signaling networks that are triggered by estradiol (E2) in isogenic MCF-7 breast cancer cells that undergo apoptosis (MCF-7:5C) versus cells that proliferate upon exposure to E2 (MCF-7). The nuclear receptor co-activator AIB1 (Amplified in Breast Cancer-1) is known to be rate-limiting for E2-induced cell survival responses in MCF-7 cells and was found here to also be required for the induction of apoptosis by E2 in the MCF-7:5C cells. Proteins that interact with AIB1 as well as complexes that contain tyrosine phosphorylated proteins were isolated by immunoprecipitation and identified by mass spectrometry (MS) at baseline and after a brief exposure to E2 for two hours. Bioinformatic network analyses of the identified protein interactions were then used to analyze E2 signaling pathways that trigger apoptosis versus survival. Comparison of MS data with a computationally-predicted AIB1 interaction network showed that 26 proteins identified in this study are within this network, and are involved in signal transduction, transcription, cell cycle regulation and protein degradation.G-protein-coupled receptors, PI3 kinase, Wnt and Notch signaling pathways were most strongly associated with E2-induced proliferation or apoptosis and are integrated here into a global AIB1 signaling network that controls qualitatively distinct responses to estrogen

Activation of Estrogen Receptor-α by E2 or EGF Induces Temporally Distinct Patterns of Large-Scale Chromatin Modification and mRNA Transcription

Estrogen receptor-α (ER) transcription function is regulated in a ligand-dependent (e.g., estradiol, E2) or ligand-independent (e.g., growth factors) manner. Our laboratory seeks to understand these two modes of action. Using a cell line that contains a visible prolactin enhancer/promoter array (PRL-HeLa) regulated by ER, we analyzed ER response to E2 and EGF by quantifying image-based results. Data show differential recruitment of GFP-ER to the array, with the AF1 domain playing a vital role in EGF-mediated responsiveness. Temporal analyses of large-scale chromatin dynamics, and accumulation of array-localized reporter mRNA over 24 hours showed that the EGF response consists of a single pulse of reporter mRNA accumulation concomitant with transient increase in array decondensation. Estradiol induced a novel cyclical pattern of mRNA accumulation with a sustained increase in array decondensation. Collectively, our work shows that there is a stimuli-specific pattern of large-scale chromatin modification and transcript levels by ER