P=0.002). The majority (12/14) of AZD5582+TRAIL-resistant cell lines retained a functional cell death pathway, as they were sensitive to AZD5582+TNFα combination treatment. This suggested that failure of the TRAIL receptor complex to transduce the death signal to Caspase-8 underlies AZD5582+TRAIL resistance. We developed a 3D spheroid assay and demonstrated its suitability for the ex vivo analysis of the Caspase-8 activity as a predictive biomarker. Altogether, our study demonstrated a link between the functionality of the TRAIL receptor pathway and the synergistic activity of the IAPi+TRA combination treatment. It also provided a rationale for development of the Caspase-8 activity assay as a functional predictive biomarker that could allow better prediction of the response to IAPi+TRA-based therapies than the analysis of expression levels of protein biomarkers.The discovery of cancer cell-selective tumour necrosis factor-related apoptosis inducing ligand (TRAIL)-induced apoptosis generated broad excitement and development of TRAIL receptor agonists (TRA) as potential cancer therapy. Studies demonstrating the synergistic combination effect of SMAC mimetics and TRA further suggested potentially effective treatment in multiple tumour settings. However, predictive biomarkers allowing identification of patients that could respond to treatment are lacking. Here, we described a high throughput combination screen conducted across a panel of 31 breast cancer cell lines in which we observed highly synergistic activity between TRAIL and the inhibitors of apoptosis proteins (IAP) inhibitor (IAPi) AZD5582 in ~30% of cell lines. We detected no difference in the expression levels of the IAPi or TRAIL-targeted proteins or common modulators of the apoptotic pathway between the sensitive and resistant cell lines. Synergistic combination effect of AZD5582 and TRAIL correlated with sensitivity to TRAIL, but not to AZD5582 as a single agent. TRAIL treatment led to significantly greater activity of Caspase-8 in sensitive than in resistant cell lines ( Moreover, even preclinical research does not offer a clear guidance on development of predictive biomarkers to TRAs;1 similarly, we are only beginning to appreciate the challenge of predicting sensitivity to IAP inhibitors.18 Furthermore, predicting the response to simultaneous interference with two different components of the apoptotic machinery (IAP and TRAIL receptors), presents additional challenge. This is at least in part because the mechanisms responsible for the death signal transduction and execution are still not completely understood in the context of the combination treatment.Predicting response to agents targeting the apoptotic pathway has proven challenging due to a high degree of complexity and redundancy in cell death pathways.ex vivo Caspase-8 biomarker analysis and confirmed feasibility of this method. Altogether our results suggest that functional biomarkers such as Caspase-8 activity as readout of the functionality of the TRAIL receptor pathway may prove superior to the analysis of protein expression, in predicting the response to IAPi+TRA combination treatment.Here, we focused our attention on identification of molecular biomarkers that define the difference between the breast cancer cell lines that are either sensitive or resistant to a combined IAPi (AZD5582) and TRAIL treatment. We performed a high throughput combination screen on a large panel of cell lines and searched for markers of sensitivity or resistance. We found no differential expression of target proteins, nor of the modulators of the apoptotic pathway tested in this study between the sensitive and resistant cell lines. However, we demonstrated that sensitivity to TRAIL, but not to AZD5582, correlated with synergistic response to the combination treatment, and that TRAIL treatment leads to a significant increase in Caspase-8 activity in sensitive, but not in resistant cell lines. We subsequently established a protocol for We performed a combination screen in a panel of 31 breast cancer cell lines to evaluate the synergism between the IAP inhibitor AZD5582 and TRAIL. We observed a high variability of phenotypic response with no synergistic tumour cell lethality in 13 cell lines (synergy score <4), strongly synergistic response and indication of enhanced cell killing in 10 cell lines (synergy score >10) and 10 cell lines showing intermediate synergy (synergy score >4 and <10) with a median synergy score of 5.1 . Additio19 reduction of cIAP1 was clearly observed at 2 and 8 h with 10 nM AZD5582 in both sensitive and resistant cell lines  and DR4 and DR5 (targets of TRAIL) . We founll lines .To investigate the mode of action of the AZD5582+TRAIL treatment in our panel of cell lines, we examined cleavage of PARP by western blotting, as readout of apoptosis. As early as 2 h after treatment, we observed enhanced cleavage of PARP in response to the combination treatment, compared with single agents in three out of five sensitive cell lines, indicating the onset of apoptotic cell death . Note thP<0.0001 . These data are further supported by western blot analysis showing Caspase-8 cleavage in sensitive but not in resistant cell lines  and MDA-MB-436 (combination sensitive) cells as 3D spheroids and subsequently subjected them to TRAIL treatment followed by the Caspase-8 activity assay. Similarly to 2D, we detected no effect in MDA-MB-361, but we observed over four-fold increase in Caspase-8 activity in MDA-MB-436 cells . We alsopheroids . Altoget1 With the potentially well-tolerated characteristics of TRAs, a significant interest has been maintained to further develop TRA-based therapeutic approaches. In this context, two major advances are required to utilise TRAs in the treatment of cancer: highly synergistic combinations with other therapeutic agents and the development of suitable predictive biomarkers for patient stratification.Initial evaluation of TRAs in human preclinical cancer models provided hope for potentially well-tolerated, tumour-specific anti-cancer therapies. However, clinical trials of a number of different TRA agents proved generally disappointing with very few clinically significant responses in patients receiving the monotherapy or chemo-combination with the TRA agents.20 This might be due to a multiplicity of other factors that determine response to TRAs. Among these, FLIP (Flice-like inhibitory protein) that functions as an inhibitor of Caspase-8 activation, overexpression and amplification of IAP, overexpression of anti-apoptotic and downregulation of proapoptotic members of Bcl2 protein family were shown to confer resistance.21 However, we observed no significant correlation between cell sensitivity and expression of key effectors and modulators of the cell death pathway. Some of the analysed proteins, the most notably proapoptotic Bim and Puma, displayed expression pattern that bordered on significance; however, their expression levels were higher in resistant cells that appear inconsistent as a resistance mechanism. On the other hand, expression levels of antiapoptotic MCL-1 were somewhat higher in resistant cell lines, however this was also not significant (P=0.07) and furthermore the direction of differential expression lacked clarity as some sensitive cells expressed increased and some resistant reduced levels of Mcl-1  out of 12 cell lines in which TRAIL as a monotherapy reduced cell viability by more than 20%.The spectrum of factors mediating resistance to TRAs is very broad and the blockade in the transduction of the death signal may occur at multiple levels of the apoptotic/cell death pathway, preventing the realisation of the clinical efficacy of TRAs. Epigenetic silencing, mutations and defective glycolysation of death receptors occurs frequently in TRAIL-resistant models; we initialised the study through profiling the target protein expression of AZD5582 and TRAIL and detected no statistically significant differences between sensitive and resistant cell lines in the breast tumour cell panel. This is consistent with reports that expression levels of TRAIL receptors are generally not predictive of the response to TRAs.of Mcl-1 . These rα, suggesting a defect in TRAIL receptor-dependent activation of Caspase-8. Signalling from TRAIL to Caspase-8 could be blocked through several mechanisms, including receptor endocytosis,23 O-glycosylation,24 expression of Galectins25 or defective assembly of the DISC.26 To by-pass the need to confirm or exclude each of these resistance mechanisms, we measured Caspase-8 activity and found that it was substantially increased in AZD5582+TRAIL-sensitive cells compared with resistant cell lines following TRAIL treatment. This suggests that measurement of Caspase-8 activity in response to TRAIL treatment alone could serve as a functional predictive biomarker for the IAPi+TRA treatment. The added benefit of measuring Caspase-8 activity is the opportunity to specifically evaluate functionality of the TRAIL receptor pathway in response to TRAIL, which we show is associated with AZD5582+TRAIL synergy . Therefore, our proposed approach based on measurements of Caspase-8 activity following TRAIL treatment has a potential to simplify the process as it is performed using a simple one-step assay following treatment with one concentration of TRAIL thus avoiding the need to measure synergy. It relies on our observations that (i) sensitivity to TRAIL as a single agent correlates with TRAIL+AZD5582 synergy, (ii) cell death pathway is generally functional downstream but defective upstream from Caspase-8 in combination resistant cell lines and (iii) functionality of the TRAIL receptor pathway can be probed and the combination effect predicted using the Caspase-8 activity assay. We also suggested an appropriate in vitro assay to allow Caspase-8 activity measurements, confimed feasibility, and optimised the work flow thus preparing a platform for future analysis of patient samples. It remains uncertain which are the key factors that determine the tumour cell sensitivity to AZD5582 as a single agent. Through the tumour cell panel profiling, we have observed a significant degree of sensitivity to the agent in a number (~30%) of cell lines  would in such cases prevent leaky activation of caspases, remains unclear, but this presents a compelling biomarker opportunity that should be explored further.Interestingly, the cell death pathway downstream of Caspase-8 appeared to be functional in AZD5582+TRAIL-resistant cell lines since the majority of these cells responded robustly to AZD5582+TNF synergy . We obse synergy . In the ll lines . Althoug41 In this report, we describe the large-scale high throughput in vitro combination screen across a broad breast cancer cell line panel and identify significant subsets of either exquisitely sensitive or completely resistant cell lines to facilitate the study of sensitive and resistance mechanisms to specific treatment. Our data provide insight into the molecular determinants that govern the response to a combined treatment of the IAP inhibitor AZD5582 and TRAIL which allowed identification of Caspase-8 as a potential functional biomarker. Clinical trials evaluating IAPi+TRA combination treatment have recently been initiated, which warrants research towards further validation and development of this biomarker to address an urgent unmet clinical need and support the development of a potentially well-tolerated and effective anticancer treatment across multiple tumour types.In conclusion, this study, as well as a large body of published evidence, suggests that analysis of basal expression of effector proteins as biomarkers may not be effective in predicting the response to IAPi+TRA treatment and instead functional assays might be required to achieve reliable predictions early in patient treatment. Development of organotypic tumour culture platforms, which is recently gaining significant traction, enables drug response prediction using patient-derived cells prepared from a biopsy material; this will likely shape future personalised cancer medicine.in vitro experiments are listed in Cell lines were from ATCC except for and HT-29, Colo741, SW620, HCA-7, C32 and C75 (ECACC) were cultured in humidified incubators at 37 °C with 5% carbon dioxide. Cell lines and culture media used for propagation and μg of protein was loaded per well and separated on gradient 4–20% Bis-Tris Criterion gels , transferred onto nitrocellulose membranes using the iBlot Dry Transfer System (Life Technologies), incubated with a blocking solution of 5% BSA in 0.05% TBST buffer and incubator overnight with primary antibodies . Protein concentration was measured using the BCA Assay , lysates were diluted with sample loading buffer  and 20 μl of 2 μmol/l Sytox Green (Life Technologies) in TBS/5 mmol/l EDTA to each well of the 384-well plates followed by incubation for 1 h at room temperature and reading on the Acumen. Subsequently, 10 μl of 0.25% saponin in TBS/5mM EDTA was added to each well, incubated at room temperature for 16 h and re-read using the Acumen as previously for the dead cells read.For the high throughput screen, 500–2500 cells were seeded per well  of data and take into consideration all the concentrations tested. The package determines the deviation of the data away from a predicted model of additivity based on the monotherapy values and assigns a synergy score according to the level of ‘excess'.g for 5 min to bring all cells into proximity at the bottom of the ‘U'-shaped well. Spheroids formed were ready for experiments within 3–4 days.Cells were harvested by trypsinisation, counted and 1000 cells was seeded per one well of a 96-well round bottom clear cell repellent plate  in normal culture media supplemented with 1% matrigel. Culture plates were subsequently centrifuged at 300 × μg/ml collagenase (Sigma) and 500 μg/ml dispase (Sigma) in serum-free media at 37 °C for 1 h with gentle rocking. Subsequently, cells were sieved through 70 μm filter, counted and 1000 cells was seeded per one well of a 96-well round bottom clear cell repellent plate (Greiner) in serum and phenol red-free Mammary Epithelial Cell Basal Medium, Promocell  supplemented with 1% matrigel. Culture plates were subsequently centrifuged at 300 × g for 5 min. Spheroids formed were ready for subsequent experiments within 3–4 days.Cells were extracted from xenografts by incubation of small tumour fragments generated by cutting with a scalpel with a mix of 1 mg/ml DNase (Qiagen), 120 μM Cellevent Caspase-3/7 reagent (Life Technologies) for 1 h at 37 °C followed by fixation with 4% PFE and staining with 1 μM Hoechst 33342 for 1 week at 4 °C. For the purpose of lightsheet microscopy (Zeiss Lightsheet Z.1) spheroids were suspended in 1% low temperature melting point agarose (Sigma), aspirated into a 2-mm-thick glass capillary insertable into the imaging chamber of the light sheet. In all, 488 and 405 nm lasers were used to excite green and blue fluorescence, respectively, the cube filter included a Laser Block Filter (LBF) 405/488/561 nm and a long-pass 490 nm dichroic mirror. Acquisition mode was set to 16 bit image, dual side fusion system, frame size 678 × 678 μm and pixel size 0.35 μm. Imaging was through the agarose core withdrawn from the capillary; Z-stack was performed to a depth of 200 μm of the spheroid and sectioned every 1 μm.Spheroids were treated with 5 Images were further processed in ZEN2014 software to display the maximum intensity projection for the z-stack multidimensional data set from spheroids. Maximum intensity projection confers the output image with the pixels that contain the maximum value over all images in a stack (a 3D construct) for a specific pixel location. All images were processed following the same protocol.Real-time evaluation of apoptotic cell death was performed using the Cellplayer kinetic Caspase-3/7 assay reagent  in cells subject to siRNA knockdown and compound treatment in 384-well Griener black clear bottomed tissue culture treated plate, imaged with Incucyte Zoom under × 20 objective for 72 h (Essen Bioscience).19 recombinant human TRAIL and the pan-caspase inhibitor Q-VD-OPh were from Sigma, and Caspase-8 Glo detection kit was from Promega, Southampton, UK.IAP inhibitor AZD5582 was described before,


A number of TP53-MDM2 inhibitors are currently under investigation as therapeutic agents in a variety of clinical trials in patients with TP53 wild type tumors. Not all wild type TP53 tumors are sensitive to such inhibitors. In an attempt to improve selection of patients with TP53 wild type tumors, an mRNA expression signature based on 13 TP53 transcriptional target genes was recently developed . Careful reanalysis of TP53 status in the study validation data set of cancer cell lines considered to be TP53 wild type detected TP53 inactivating alterations in 23% of cell lines. The subsequent reanalysis of the remaining TP53 wild type cell lines clearly demonstrated that unfortunately the 13-gene signature cannot predict response to TP53-MDM2 inhibitor in TP53 wild type tumors.DOI:http://dx.doi.org/10.7554/eLife.10279.001 Damaged cells in the human body can develop into tumors if left unchecked. TP53  is a protein that normally helps to repair or eliminate these damaged cells and prevent tumors from forming. About half of all cancerous tumors have mutations that prevent TP53 from working. In tumors with normal TP53 , another protein that acts to keep TP53 in check is often overly active. This overactive protein  prevents TP53 from suppressing tumor development. Many scientists are developing anticancer drugs called TP53-MDM2 inhibitors to target the potentially overactive protein in TP53 wild type tumors, and importantly only a tumor with working TP53 would have a chance of responding to this kind of inhibitor.Earlier in 2015, a team of researchers at the Novartis Institutes for BioMedical Research reported the results of a screen of hundreds of cancer cell lines that investigated which ones were sensitive to TP53-MDM2 inhibitors. Using mix of TP53 mutant and TP53 wild type cancer cell lines, the Novartis team identified a set of 13 genes that were highly expressed in cell lines that were sensitive to one of these inhibitors. This 13-gene signature was then suggested as a way to identify which cancer patients with TP53 wild type tumors would be the most likely to benefit from treatment with TP53-MDM2 inhibitors.However, now Dmitriy Sonkin has reanalyzed the validation set of TP53 wild type cancer cell lines used by the Norvartis team and found that many of them had been mistakenly identified as TP53 wild type. That is to say around a quarter of the cell lines thought to have normal TP53 actually had mutations in the gene for TP53. Sonkin then repeated the analysis using only those cell lines that were from TP53 wild type tumors. This revealed that the 13-gene signature cannot predict how cancer cells from a TP53 wild type tumor will respond to a TP53-MDM2 inhibitor. Further work would be beneficial in order to find an accurate test to determine which cancer patients will benefit the most from treatment with TP53-MDM2 inhibitors.DOI:http://dx.doi.org/10.7554/eLife.10279.002 A number of TP53-MDM2 inhibitors are currently under investigation as therapeutic agents in a variety of clinical trials across multiple tumor types. Mechanistically, only tumors with wild-type (WT) TP53 can potentially be sensitive to TP53-MDM2 inhibitors as confirmed in part by sensitivity of WT MEFs cells and by the loss of sensitivity in TP53 knockout MEFs . TherefoRecently, One potential explanation for the reported predictive ability of the As can be seen in In order to re-evaluate the performance of the signature in TP53 WT settings, the 12 cancer cell lines with inactivated TP53 listed in As can be seen from In clinical sequencing, special care is taken to make sure sufficient coverage is obtained across all target regions in order to reliably detect point mutations, insertions/deletions, fusions and copy number aberrations . Often tIn addition to providing sensitivity to NVP-CGM097 in the validation set, Based on the current analysis, it is clear that the In summary, it is clear that NVP-CGM097 and NVP-CFC218 pharmacologic cell line profiling data, 13-gene signature predictions have been obtained from .http://www.broadinstitute.org/ccle/home). TP53 mutation calls have been obtained from the following two files: CCLE_hybrid_capture1650_hg19_NoCommonSNPs_NoNeutralVariants_CDS_2012.05.07.maf (22-May-2012) and 1650_HC_plus_RD_muts.maf.annotated (24-Nov-2014), both files are available for download from CCLE website. Genomic characterization section in Supplementary methods  ratio is the ratio of signal intensity in a tumor sample versus normal reference samples normalized to total DNA quantity; thus a CN ratio of 1 corresponds to a diploid locus. CN ratio <0.6 indicates ‘allelic loss’. CN ratio <0.25 indicates ‘bi-allelic loss’.All mRNA expression values are MAS5 normalized, with a 2% trimmed mean of 150 . TP53 Af In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.eLife. Your article has been reviewed by two peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Tony Hunter as the Senior Editor.Thank you for submitting your work entitled "Expression signature based on TP53 target genes doesn't predict response to TP53-MDM2 inhibitor in wild type TP53 tumors" for consideration by The reviewers have discussed the reviews with one another and the Reviewing editor has drafted this decision to help you prepare a revised submission.The current report by Sonkin challenges the conclusions of a recent paper by Jeay et al. reporting the discovery of a gene signature that could potentially predict the efficacy of small molecule inhibitors of the p53-MDM2 interaction in the treatment of tumors expressing wild-type p53. Upon reanalysis of the p53 mutational status of the cell lines employed, Sonkin determined that Jeay et al. had not assessed the mutational status of p53 correctly for a number of cell lines. When the analysis is repeated with the annotation by Sonkin, the gene signature no longer predicts drug efficacy, simply discriminating between wild-type and mutant cell lines. In this regard, the report by Sonkin is important, as it challenges some of the main conclusions in the report by Jeay et al. about the utility of the gene signature.Having said that, it is surprising and unfortunate that neither the original nor the present paper has a clear description of how the variants were called. The original paper says, in the Materials and methods that "gene level genetic alterations […] were compiled from the Sanger center COSMIC data and internal sources including Exome Capture Sequencing of 1600 cancer related genes", but it does not say exactly what methods were used to call and/or validate variants. Likewise, the present paper simply states: "Careful examination of TP53 status identified 12 out of 52 cancer cell lines containing TP53 alterations…".It is then necessary for Sonkin to provide additional evidence for the mutations he found, just so that the reader can better understand why Jeay et al. missed them. Based on In brief, a more thorough discussion of the various methodologies employed for variant calling and an effort to explain why Jeay et al. and the public databases are producing different results from those obtained by Sonkin would be required to advance publication of this work, whose potential impact is very high, as it would not only challenge the paper by Jeay et al., but also public databases employed by thousands of researchers around the world. […] Having said that, it is surprising and unfortunate that neither the original nor the present paper has a clear description of how the variants were called. The original paper says, in the Materials and methods that "gene level genetic alterations […] were compiled from the Sanger center COSMIC data and internal sources including Exome Capture Sequencing of 1600 cancer related genes", but it does not say exactly what methods were used to call and/or validate variants. Likewise, the present paper simply states: "Careful examination of TP53 status identified 12 out of 52 cancer cell lines containing TP53 alterations…".All cell lines referenced in the manuscript were part of Cancer Cell Line Encyclopedia (CCLE) and therefore I used publicly available CCLE mutation calls . The manuscript was modified to make it clear that publicly available TP53 CCLE mutation calls have been used (Results and Discussion). I’ve modified the Materials and methods to reference exact two CCLE files from CCLE website which were used as source of TP53 mutation calls and also provided reference to genomic characterization section provided by Barretina et al., which includes detailed description of sequencing data generation and variant calling pipeline.It is then necessary for Sonkin to provide additional evidence for the mutations he found, just so that the reader can better understand why Jeay et al. missed them. Based on Indeed Sanger Institute COSMIC databases are extremely valuable resource and used by thousands of researchers around the world. COSMIC database contains sequencing data for 8 out of 10 cell lines with TP53 mutations listed in References:Klijn, C., Durinck, S., Stawiski, E.W., Haverty, P.M., Jiang, Z., Liu, H., Degenhardt, J., Mayba, O., Gnad, F., Liu, J., et al. (2015). A comprehensive transcriptional portrait of human cancer cell lines. Nat. Biotechnol. 33, 306–312.


Aggregation raises attention in Nanotoxicology due to its methodological implications. Aggregation is a physical symptom of a more general physicochemical condition of colloidal particles, namely, colloidal stability. Colloidal stability is a global indicator of the tendency of a system to reduce its net surface energy, which may be achieved by homo-aggregation or hetero-aggregation, including location at bio-interfaces. However, the role of colloidal stability as a driver of ENM bioactivity has received little consideration thus far. In the present work, which focuses on the toxicity of nanoscaled Fe° nanoparticles (nZVI) towards a model microalga, we demonstrate that colloidal stability is a fundamental driver of ENM bioactivity, comprehensively accounting for otherwise inexplicable differential biological effects. The present work throws light on basic aspects of Nanotoxicology, and reveals a key factor which may reconcile contradictory results on the influence of aggregation in bioactivity of ENMs. Pristine nZVI powder showed a partial degree of surface oxidation as revealed by XRD analysis (Table S1). This is due to the high tendency of zero valent iron to oxidize in aerobic conditions −1 were prepared in Milli-Q water and OECD TG 201 algal growth medium −1 to −27.5 mV for 25 mgL−1. The observed tendency of nZVI to acquire negative charge in saline medium has been associated with the high affinity of ions to be adsorbed onto the oxy-hydroxide surface shell of nZVI formed under oxidant conditions −1 nZVI suspensions showed a high degree of agglomeration (−1) allowed us to observe primary sized particles and small particle aggregates . XEDS (X-Ray Energy Dispersive Spectroscopy) analysis confirmed Fe as the main constituent of the visualized particles (−1 of nZVI in Milli-Q water had the lowest polydispersity index (PDI) and effective diameter  with the initial dosage . In this narrow interval nZVI appeared suspended in its primary size (4–12 nm) along the experimental lapse time  at relevant experimental lapse times Pseudokirchneriella subcapitata (P. subcapitata) p<0.05) (p>0.05) regions of toxic response, bracketing a non-toxic region. The first toxic dose region occurred within nZVI concentrations of 0.05 to 0.075 mgL−1, resulting in almost 40% maximum growth inhibition. The second window of concentrations resulting in adverse biological effects ranged from 1.0 to 2.5 mgL−1, resulting in almost 60% maximum growth inhibition (p>0.05) increase in intracellular ROS production, and cell cycle alterations  from early stages of nZVI exposure (24 h) (−1), coinciding with the colloidal singularity described earlier  . These changes consisted of a significant reduction of peak absorption at wavenumbers characteristic of asymmetric (2924 cm−1) and symmetric (2853 cm−1) sp3 C-H stretching vibrations, O-H stretching (3222 cm−1) and bending (1654 cm−1) vibrations in hydroxyl functional groups and C = O stretching vibration (1743 cm−1) of carbonyl functional groups −1 treatment  in ζ- potential which typically account for aggregation and sedimentation of colloidal particles colloidal singularity was induced by neutralizing the negative surface charge density of the 0.5 mgL−1 nZVI suspension by using a classical hydrolyzing metal coagulant [Al2(SO4)3] 3+, like other polyvalent metal cations, is specifically adsorbed on negatively charge surfaces, thereby reducing the surface charge density 2(SO4)3 (2(SO4)3 was chosen, as it proved to effectively reduce the ζ-potential of the 0.5 mgL−1 nZVI suspension from −28 mV to nearly −10 mV, resulting in partial colloidal destabilization. This Al2(SO4)3 had no detrimental effect on the growth of P. subcapitata2(SO4)3 to the test system containing 0.5 mgL−1 nZVI caused 2-fold reductions in the growth rates of P. subcapitata (p>0.05) (p>0.05) increase in sedimentation rates (p>0.05)  specifically adsorb on the negatively charged surface of the suspended colloids. This results in a characteristic non-linear behavior on the residual turbidity of the suspensions as a function of the resulting colloid/ions ratio. The classical flocculation diagram presents three differential stages: (1) in a first stage, the dose of coagulant is not enough to destabilize the colloids which remained negatively charged and stable. (2) With increasing coagulant concentrations, the adsorbed cations effectively reduce the surface charge of suspended colloids, resulting in colloidal destabilization and removal of colloids. This typically happens in a very narrow coagulant dosage vs nZVI dose diagrams, we did not find charge reversal causing stabilization of nZVI in the colloidal singularity, but rather an increase in its electrophoretic mobility . We hypothesized that the high affinity of anions to be adsorbed on nZVI surfaces colloidal singularity dose range This would result in a net increase in negative surface charge and may cause a reduction of its net surface energy, and of its tendency to interact with bio-interfaces.When suspensions of nZVI were prepared in OECD culture medium, we observed an ENM speciation phenomenon colloidal singularity), no detrimental biological effects could be observed. This was true even when its total surface area was higher than that of any aggregated nZVI suspension. This is in apparent disagreement with previous reports 2(SO4)3.The occurrence of the colloidal singularity is highly illustrative as a case study for EHS of ENMs. It clearly exemplifies the extreme relevance of ENMs speciation in their ability to interact with living organisms, resulting in differential biological effects P.subcapitata is linked to the production of ROS, cell cycle alterations and pre-apoptotic DNA fragmentation; and therefore can be assigned to the oxidative stress toxicity paradigm microalgae, including P. subcapitata. However, the investigation of the underlying toxic mechanism was beyond the scope of their study. ROS mediated toxicity of nZVI is consistent with previous studies with other biological model systems, including bacteria, fish and mammals P. subcapitata control cells markedly resemble those of cyclic sugars P. subcapitata cell wall. This suggests the presence of active binding sites of nZVI to P. subcapitata cell wall. The latter may imply that nZVI is able to induce intracellular specific toxic responses by damaging the structure and changing the physicochemical properties of surface biomolecules 2O3, TiO2 and ZnO) induced chemical and structural changes on bacterial cell envelopes, and that toxicity correlated with the severity of those changes. Similarly, other authors have found direct bond-interaction of oxide nanoparticles with algal and bacterial cell walls mediating toxicity and ROS C. vulgaris is especially interesting. They found that toxicity of NiO nanoparticles was mediated by hetero-aggregation. Furthermore, they found a decrease in the NiO signal and the appearance of a Ni° peak in the X-Ray diffraction spectra of NiO nanoparticles attached to the cell walls. This evidenced that a redox reaction was occurring between the NiO surface and the cell walls, resulting in the reduction of Ni (II) to Ni° 1) i.e., a Fenton/Haber–Weiss reactions P. subcapitata. We hypothesize that the spontaneous bio-reduction of some of the surface iron oxy-hydroxides by microalgal surface biomolecules, might be the origin of the attachment of nZVI to P. subcapitata. This may result in concomitant ROS induction and cell cycle alterations which is in agreement with the oxidative stress paradigm of redox cycling at the bio-interface Nanoparticle-induced oxidative stress caused by the formation of reactive oxygen species (ROS) has been established as one of the most common paradigms involved in the toxic responses induced by engineered nanoparticles in living organisms microalgae and other aquatic microorganisms in the “colloidal” size region. From our results, surface charge seems to play a major role in these negative-negative interactions because an increase  of nearly 10 mV (from −15 mV to −25 mV) seems to be enough to prevent hetero-aggregation. Similarly, a reduction from −25 mV to −14 mV was enough to induce it. However, would all ENMs and organisms have the same intrinsic tendency to generate hetero-aggregation? Logic seems to indicate that probably not. However, the rules governing the interactions between negatively charged colloids and organism interfaces remain unclear From our results, it can be inferred that colloidal stability is a crucial regulator of the interaction of negatively charged ENMs with bio-interfaces. In this regard, there is a huge number of published research reporting toxicity of a variety of negatively charged metallic and carbonaceous ENMs on aquatic organisms in-vitro. Firstly, when performing EHS screening From a basic methodological view-point, our findings have some broader implications for EHS evaluation of ENMs colloidal singularity. Basically, nZVI generally appeared in the form of aggregates. However, there was a narrow dose-range , between 0.1–0.5 mgL−1 nZVI where it appeared highly stable . nZVI resulted in adverse biological effects when destabilized, but not when stable . Furthermore, destabilization of those particular suspensions resulted in toxicity. Considering colloidal stability as a driver of bio-physical interactions allows us to explain our findings and previous apparently contradicting reports. In summary, our work demonstrates the role played by colloidal stability as a fundamental driver of ENM bioactivity, and opens up new perspectives on the relevant factors which may be considered in EHS and bioactivity testing of ENMs.The influence of physicochemical state on the bioactivity and toxicity of ENMs is presently under discussion. In the present work, when a linear nZVI dose-range was prepared for EHS characterization, a spontaneous speciation phenomenon occurred which resulted in a qualitatively different physicochemical state of nZVI along the dose gradient. We called it −1) were prepared in Milli-Q water followed by a 10-minute sonication bath  to avoid particle agglomeration or aging. 25 mgL−1 of nZVI in Milli-Q water was selected as stock suspension since it had the lowest polydispersity index (PDI) and effective diameter  powder was purchased from Quantum-Sphere . The water used throughout the work was Milli-Q water. nZVI stock suspensions (25 mgLdiameter Table 1 in situ injection of large quantities (up to 50 g nZVI/L) into the subsurface waters The current use of nZVI particles in the remediation of water resources contaminated with recalcitrant organic pollutants is based on The Nova 1200 BET (Brunauer –Emmett –Teller) was used to determine the surface area of pristine nZVI. Morphology properties were studied by Transmission Electron Microscopy (TEM) at 200 KeV operating voltage in a JEOL JEM 2100 electron microscope with 0.25 nm point resolution coupled with XEDS (X-Ray Energy Dispersive Spectroscopy). ENMs size measurements, interplanar spacing of crystalline planes and Fast Fourier Transform (FFT) power spectrums were analyzed using Digital Micrograph software, 2.30.542.0 (Gatan Inc.). The size distribution of nZVI was obtained using dynamic light scattering . Measurements were conducted performing 500 rounds measurements and in particle number mode. ς-potential was measured via electrophoretic light scattering combined with phase analysis light scattering in the same instrument. ζ-potential was derived from electrophoretic mobility by applying the Henry equation and the Smoluchowski approximation Table S2.). Samples were maintained under identical experimental conditions as the bioassays. The temporal stability of nZVI particles was evaluated by measuring the residual absorbance at λ = 750 nm. 25 mL of samples were carefully taken from the supernatant of the test flasks to prevent catching sedimented non-colloidal nZVI fractions. Absorbance measurements were performed in 100 mm light path spectrophotometric glass cuvettes . Main physicochemical properties of nZVI colloidal fractions were evaluated by measuring ζ-potential and DLS of the supernatant of the test flasks. Total surface area (SSA) was calculated accordingly to the −3 accordingly to producer) and d is the effective diameter of the particles.The suspension stability of nZVI particles was measured over time  by spectrophotometry . 250 mL of the desired nZVI concentrations were prepared in OECD TG 201 algal growth medium in 500 mL Erlenmayer flasks  was purchased from Microbiotests. Inc. (Denmark). P. subcapitata was routinely grown in 250 ml flasks at 28°C in light, ca. 65 µmol photons m2 s−1 on a rotatory shaker at 135 rpm in OECD TG 201 standard algal culture medium Table S2.) . Exposure experiments to nZVI suspensions were carried out in 12 mL of OECD TG 201 culture medium in 25 mL glass Erlenmeyer flasks. Before exposure to nZVI, cultures were washed once and re-suspended in fresh culture media to obtain a final optical density (ODλ = 750 nm) of 0.1. nZVI was added to achieve the desired concentrations, and cultures were exposed for up to 72 h in a rotary shaker at 135 rpm and 28°C under constant illumination. Growth inhibition experiments were performed in triplicate with serial dilutions essentially as described in the standard OECD TG 201 λ = 750 nm, total chlorophyll content and in-vivo chlorophyll fluorescence. ODλ = 750 nm was determined by spectrophotometry in a Hitachi U-2000 spectrophotometer (Japan) by measuring the culture absorbance at λ = 750 nm in 10 mm light path transparent plastic cuvettes. For nZVI nominal concentrations lower than 5 mg/L no interference of nZVI was observed in the determination of ODλ = 750 nm of P. subcapitata (data not shown). For chlorophyll content determinations, culture aliquots (250 µL) were extracted in methanol at 4°C for 24 h in darkness. The total chlorophyll content of the extract (chlorophyll a+b) was determined by spectrophotometry as described elsewhere The green alga P. subcapitata was assessed by using the fluorescent probe 2′,7′-dichlorofluorescein diacetate (H2DCFDA) . The intracellular oxidation of H2DCFDA generates 2,7-dichlorofluorescein (DCF), a fluorescent compound that serves as an indicator for hydrogen peroxide and other ROS, such as hydroxyl and peroxyl radicals. A 100 mM H2DCFDA stock solution was freshly prepared in DMSO under dim light conditions to avoid degradation. Prior to analysis, the green alga was incubated for 30 min at room temperature (23°C) with a final concentration of 100 µM of H2DCFDA. As a positive control for ROS formation, 3% H2O2 (v/v) was used. Fluorescence was monitored on a Synergy HT multimode microplate reader  with excitation and emission wavelengths of 488 and 530 nm, respectively. Results were normalized, for differences in cell numbers, by measuring chlorophyll content (as described previously) and expressed as arbitrary fluorescence units (AFU) per µg of chlorophyll a+b.Intracellular reactive oxygen species (ROS) produced by −1 and at least 10,000 events  were recorded. Light scattered by cells was collected at two angles: FS and SS, which were used in combination to distinguish between different cell populations. Non-algal particles were excluded from the analysis by setting an acquisition threshold value 1 for the FS parameter. Chlorophyll red autofluorescence was collected with a 675 nm long band pass filter (FL4), PI fluorescence was collected with a 575 nm long band pass filter (FL2), and the signal was adjusted to exclude the residual fluorescence signal coming from the chlorophyll red autofluorescence (FL4) (data not shown). Data acquisition was performed using MXP-2.2 software, and the analyses were performed using CXP-2.2 analysis software. Fluorescence was analysed in Log mode (chlorophyll fluorescence) and linear mode (PI fluorescence).Alterations in cell cycle were assessed by propidium iodide (PI) staining and flow cytometry analysis using a Cytomix FL500 MPL flow cytometer . 1 mL of cell suspensions of the nZVI exposure experiments were collected in 1.5 mL eppendorf tubes and fixed by adding 3% paraformaldehyde . Samples were kept in darkness at 4°C until further preparation. For PI staining, cells were gently washed with 1 mL PBS and were incubated for 3 h at 37°C in 1 mL of 0.05% Triton X-100, 0.24 mg/mL RNAase A  in PBS buffer for membrane permeabilization. Cells were stained in 250 mL of staining buffer consisting of 0.05% Triton X-100, 0.24 mg/mL RNase A and 40 µg/mL PI and were incubated for 24 h in the dark at 4°C. Nuclear DNA content was then analysed using a Cytomics FC500 MPL flow cytometer with the MXP software  equipped with an argon-ion excitation wavelength (488 nm). The flow rate was set at 1 µL s2 glass cover-slips and were dried for 2 h at 25°C. Infrared spectra of the algal cell before and after nZVI contact experiments were obtained using a Bruker model IFs 66VFourier Transform Infrared (FTIR) spectrometer in transmission mode. This analysis allowed us to track changes in the chemical bonds and to elucidate the chemical groups involved in nZVI sorption processes.For transmission electron microscopy (TEM) analysis, algal cell suspensions exposed to nZVI were collected by centrifugation using a swinging bucket rotor at low relative centrifugal forces (RCFs = 1500 g) during 3 min in order to reduce the chance of artifacts algal suspensions was evaluated by measuring ζ-potential, DLS and sedimentation rates of the colloidal system integrated by the algal cells and nZVI. For the determination of the sedimentation rates, a sedimentation system consisting of 15 mL falcon tubes was used. Algae exposed to the different nZVI concentrations were collected and ODλ = 750 nm were determined by spectrophotometry . All colloidal systems were leveled to a homogeneous ODλ = 750 nm of 0.350 with a final volume of 5 mL, therefore sedimentation rates were neither influenced by differences in initial optical densities nor test symmetry (mainly water column height). Residual turbidity (ODλ = 750 nm) of the test systems was measured spectrophotometrically as previously described by taking 250 µl of the near meniscus region of the test tubes at specific time intervals  and measuring the ODλ = 750 nm. Sedimentation rates were derived from the differences in residual turbidity of the test systems as a function of time according to i-jμ is the average specific sedimentation rate (h−1) from time i to j, Xj and Xi are the residual optical density at λ = 750 nm (ODλ = 750 nm) at times i to j; and tj and ti are time (h). ζ-potential of cells exposed to nZVI samples were measured at the end of the exposure experiments. For that, 2 mL of exposed cells were collected and transferred to 2.5 mL eppendorf tubes and ζ-potential was measured directly via electrophoretic light scattering combined with phase analysis light scattering in a Malvern Zetasizer Nano ZS as describe above.Colloidal stability of nZVI-−1 of freshly prepared nZVI as described in the toxicity exposure experiments. 0.01 µM of Al2(SO4)3×18 H2O  was added to the test flask at the beginning of the experiments in order to induce colloidal destabilization and heteroaggregation of the nZVI-algal system. Growth inhibition, sedimentation rates and ζ-potential of the colloidal systems were measured as described above. The concentration of Al2(SO4)3 used for the colloidal destabilization experiments was selected based on the results of a titration experiment of 0.5 mgL−1 of nZVI suspended in OECD TG 201 algal growth medium with increasing concentrations of Al2(SO4)3 (2(SO4)3 was selected due to its ability to partially neutralize the negative surface charges of nZVI (0.5 mgL−1) without causing total neutralization or charge reversal.nZVI Destabilization experiments were performed in 15 mL Erlenmeyer flask containing 12 mL OECD TG 201 culture medium. Algal cells were exposed to 0.5 mgLpost-hoc test was performed for comparing means of the toxicity effect and physicochemical characteristic among different nZVI concentrations. Statistically significant differences were considered to exist when p<0.05.All the experimental procedures were performed at least in triplicate. The mean and standard deviations (SD) were calculated for each parameter. Statistical analyses were evaluated by R statistical program. A one-way ANOVA coupled with Student–Newman–Keuls Figure S1X-Ray diffraction (XRD) of pristine nZVI powder. X-ray diffraction analysis of pristine nZVI powder showed peaks of Fe° (Fe) and iron oxide formation of magnetite/maghemite (Fe3O4/γ-FeOOH) (M) respectively.(DOCX)Click here for additional data file.Table S1Size of nZVI primary particles and aggregates by TEM microscopy.(DOCX)Click here for additional data file.Table S2Chemical composition of OECD TG 201 standard algal culture medium.(DOCX)Click here for additional data file.


Real-time three-dimensional echocardiography (RT3DE) enables accurate volume determination of the left ventricle (LV), since measurements in foreshortened depicted views are avertable. Different analyzing programs are available for this RT3DE. The commonly used semi-automatic software 4D-AutLVQ™ showed underestimation of LV volumes in comparison with CMRI in healthy anesthetized dogs (Am J Vet Res 74(9):1223–1230, 2013). TomTec 4D LV-Function™ is an offline analysis program for morphological and functional analyses of the left ventricle by using manual measurement optimization, showing excellent agreement with CMRI in human medicine (Echocardiography 27(10):1263–1273, 2010; Eur J Echocardiogr 11(4):359–368, 2010; Echocardiography 24(9):967–974, 2007). The aim of the present study was to compare these different RT3DE analyzing software programs to test the possibility of one performing better than the other by assessing accuracy and reproducibility in comparison with the reference method cardiac magnetic resonance imaging (CMRI) by determining the left ventricular end-diastolic volume (EDV), end-systolic volume (ESV), stroke volume (SV) and ejection fraction (EF).RT3DE and CMRI were performed during anesthesia in 10 healthy beagles. The analyzing programs 4D-AutLVQ™ (based on semi-automated border detection) and TomTec 4D LV-Function™  were used for RT3DE volume analysis of the left ventricle. Left ventricular EDV, ESV, SV and EF were measured and compared to those measured by the reference method CMRI. Repeated measurements were performed to determine inter- and intra-observer variability.r = 0.34–0.69) in comparison with CMRI, without significant difference between each of them. Ejection fraction (EF) measured by 4D-TomTec™ showed no significant differences compared to CMRI (p = 0.12), while 4D-AutLVQ™ significantly underestimated LV-EF (p = 0.03). Analyzing time was shorter using 4D-AutLVQ™ compared to 4D-TomTec™. The inter-observer variability was higher using 4D-TomTec™ than with 4D-AutLVQ™, whereas both methods present excellent intra-observer variability.Both, 4D-AutLVQ™ and 4D-TomTec™ showed small but significant underestimation for EDV and ESV with quite good correlation (4D-TomTec™ and 4D-AutLVQ™ are feasible RT3DE analyzing programs, allowing accurate volume quantification of the left ventricle, albeit with significant underestimation of ventricular volumes in comparison with the gold standard CMRI. 4D-AutLVQ™ is performed faster with less inter-observer variability than 4D-TomTec™. Therefore, 4D-AutLVQ™ is the more practicable measurement method when comparing the different analyzing programs. Acquired heart disease is common in veterinary medicine. Echocardiography is a commonly used technique in routine veterinary cardiology to diagnose congenital as well as acquired heart diseases . One impThis study was permitted by the Ethical Committee of the Lower Saxony State Office for Consumer Protection and Food Safety (33.9-42502-05-11A133). 10 healthy beagles, owned by the Small Animal Hospital of the University of Veterinary Medicine Hannover, were used in this study . To ensure healthiness each dog underwent an extensive preliminary examination, including general examination, chest-radiography, electrocardiogram (ECG), blood pressure (BP) measurement, standard echocardiography and blood examination including CPC and serum chemical analyses.2 of between 40 and 45 mmHg. Isoflurane concentration and oxygen saturation were continuously measured with a calibrated monitor.h (5 ml/kg/h). The dogs were kept warm by underfloor heating and a heating jacket.9On examination day, each dog underwent an echocardiographic examination following CMRI procedure. Each dog was premedicated with diazepamEchocardiographic examinations were performed by one investigator (S.O.H.), using a commercially available ultrasound unit,11RT3DE image acquisition was performed as recommended in the Guidelines of the American Society of Echocardiography from left apical using harmonic mode . Sound fl. The software was purchased in addition to the software of the ultrasound device and was integrated into the workstation (EchoPAC). Therefore measurements could be performed with the same data sets as used for 4D-AutLVQ™. Starting the analyzing program, the left ventricle was displayed in four different views in a quad-screen  and the standard deviation of the differences using the Bland-Altman method. The strength of relation between each RT3DE analyzing technique and CMRI reference values was expressed by Pearson correlation. Correlations were defined as excellent with r ≥ 0.9, very good with r < 0.9 and ≥ 0.7, good with r < 0.7 and ≥ 0.5, less good r < 0.5 and ≥ 0.3 and weak with r < 0.3. Inter-observer and intra-observer variability was expressed as mean difference ± SD. An intra-class correlation coefficient was calculated and assessed using the following scheme: ≤ 0.1 poor agreement, > 0.1 and ≤ 0.2 weak agreement, > 0.2 and ≤ 0.4 moderate agreement, > 0.4 and ≤ 0.6 average agreement, > 0.6 and ≤ 0.8 good agreement, > 0.8–1.0 almost perfect agreement. Values of time exposure for RT3DE analyses were assessed using a paired t-test and were expressed as mean ± SD.Commercially available software programs19The blood parameters of all examined dogs were in the normal range. X-rays showed no signs of congestion and the heart size was normal  with a mp = 0.0057, bias 7.17) and 4D-AutLVQ™ . Correlation with CMRI was stronger with 4D-TomTec™ (r = 0.69) than with 4D-AutLVQ™ (r = 0.48). The underestimation was slightly but not significantly less with 4D-TomTec™ (EDV = 31.78 ± 5.35) than with 4D-AutLVQ™ (EDV = 29.97 ± 4.75) with small bias  and very good correlation (r = 0.80) when comparing the echocardiographic methods.In comparison with CMRI (EDV = 37.14 ± 2.69 ml) there was significant underestimation of EDV with 4D-TomTec™  and 4D-AutLVQ™ . In contrast to the measurement of EDV the correlation was stronger with 4D-AutLVQ™ (r = 0.48) than with 4D-TomTec™ (r = 0.34). The underestimation was slightly but not significantly less with 4D-TomTec™ (ESV = 14.89 ± 5.52) than with 4D-AutLVQ™ (ESV = 13.50 ± 3.53) with small bias  and excellent correlation (r = 0.94) when comparing the echocardiographic methods.In comparison with CMRI (ESV = 19.68 ± 2.82 ml) there was significant underestimation of ESV with 4D-TomTec™  and weak correlation (r = 0.18). 4D-TomTec™ values  were not significant higher than CMRI with weak correlation (r = −0.24) as well. There was no difference and small bias  and good correlation (r = 0.61) when comparing the echocardiographic methods.In comparison with CMRI (EF = 47.22 ± 4.45) 4D-AutLVQ™ measurements showed significantly higher EF values  or with 4D-AutLVQ™ . CMRI measurements correlated weakly with 4D-AutLVQ™ (r = −0.24) and with 4D-TomTec™ (r = −0.24). Furthermore, there was no difference when comparing both echocardiographic methods  with less good correlation (r = 0.42).In comparison with CMRI (SV = 17.46 ± 1.10 ml) there was no significant difference for SV either with 4D-TomTec™ (p < 0.0001) shorter using 4D-AutLVQ™ (145 ± 57 sec) compared to 4D-TomTec™ (215 ± 46 sec). If 4D-AutLVQ™ was carried out without manual correction, the measurement time was reduced even more  to approximately a fourth of the time using 4D-TomTec™.The time needed for volume-analysis Table  was signIndeed, the volume quantification of 4D-AutLVQ™ without manual correction was significantly faster than with all other methods, but the left ventricular volumes  were not only significantly lower compared to CMRI but also significantly lower than using the other echocardiographic methods Tables  and 4. ERegarding the inter-observer variability Table  there weRT3DE is a modern technique allowing volume determination of the left ventricle . UnderesIn this study, both analyzing programs show small but significant underestimations when measuring EDV and ESV, most likely caused by worse spatial and temporal resolution than the reference method CMRI , 23. RedAnother part of the volumetric analysis is the evaluation of LV function by SV and EF. 4D-TomTec™ showed comparable LV function parameters with gold standard CMRI. This is due to systematic underestimation of EDV as well as ESV. Using 4D-AutLVQ™ there was no difference considering SV but the EF was significantly higher when measured by CMRI as opposed to 4D-TomTec™. Therefore, the evaluation of LV function by SV and EF by means of 4D-TomTec™ and 4D-AutLVQ™ is comparable with the gold standard CMRI.A considerable disadvantage of manual volume correction is the significantly higher measurement time, which has been demonstrated in this study and is in agreement with human studies . The measurement time with manual optimization using 4D-TomTec™ is significantly longer than using 4D-AutLVQ™ without any significant advantage regarding the measurement results. In contrast, using 4D-AutLVQ™ without manual correction is by far the quickest method, this technique underestimates the LV volumes even more than 4D-AutLVQ™ with manual correction. Consequently, with regard to measurement time and accuracy 4D-AutLVQ™ with manual optimization is the method with best agreement with CMRI.The inter-observer variability 4D-AutLVQ™ (<11 %) is superior to 4D-TomTec™ (<20 %). This may be due to the more detailed options for LV ventricle depiction using 4D-TomTec™, resulting in higher variability of endocardial border detection caused by user dependent optimizations of contrast and brightness settings. Considering the different levels of experience  of the two observers the inter-observer variability itself is quite low. The excellent intra-observer variability (<3 %) using both measurement methods provides a further evidence that the inter-observer variability is caused by the differing assessment of the endocardial border by the two investigators and not by the software itself. Therefore, repeated measurements should be preferably performed by the same observer.Limitations of this study are the low number of patients, as well as the exclusive examination of anesthetized healthy beagles. Also influences of prolonged anesthesia and of differences in patient positioning on measurement results cannot be ruled out. Furthermore reproducibility and repeatability was only determined for the analysis of the data and not for the acquisition of the data. Further studies examining awake dogs of different breeds and body-weights as well as of dogs with heart disease are necessary to evaluate the utility of RT3DE in veterinary cardiology.In summary, the results of this study demonstrate that both RT3DE volumetric analysis programs show underestimation of LV volumes with appropriate evaluation of LV function in comparison with gold standard CMRI. Considering duration of measurement and inter- and intra-observer variability time 4D-AutLVQ™ is superior to 4D-TomTec™. Therefore further studies of RT3DE in dogs should be performed preferably with 4D-AutLVQ™.


Mir-9-3p transfection resulted in reduced in vitro cell viability; an effect mediated through autophagy inhibition. This was accompanied by evidence of G2 arrest in the TT cell line and increased apoptosis in both cell lines. Atg5 was validated as a predicted miR-9-3p mRNA target in TT cells. Post-miR-9-3p transfection array studies showed a significant global decline in autophagy gene expression . Autophagy gene mRNAs were generally overexpressed in sporadic (vs. hereditary MTC) and Beclin-1 overexpression was shown to correlate with residual disease. Autophagy is a tumor cell survival mechanism in MTC that when disabled, is of therapeutic advantage. Beclin-1 expression may be a useful prognostic biomarker of aggressive disease.Micro-RNAs are dysregulated in medullary thyroid carcinoma (MTC) and preliminary studies have shown that miRNAs may enact a therapeutic effect through changes in autophagic flux. Our aim was to study the in vitro effect of miR-9-3p on MTC cell viability, autophagy and to investigate the mRNA autophagy gene profile of sporadic versus hereditary MTC. The therapeutic role of miR-9-3p was investigated in vitro using human MTC cell lines (TT and MZ-CRC-1 cells), cell viability assays, and functional mechanism studies with a focus on cell cycle, apoptosis, and autophagy. Post-miR-9-3p transfection mRNA profiling of cell lines was performed using a customized, quantitative RT-PCR gene array card. This card was also run on clinical tumor samples (sporadic:  RET gene mutation status and clinical phenotype RET gene mutation within the context of MTC 20 years ago forced a paradigm shift in the way in which clinicians now manage this disease RET, however, there remains a void in our understanding of the molecular biology of SMTC.Medullary thyroid cancer (MTC) accounts for 3–10% of all thyroid malignancies and can be classed as “sporadic”  or “hereditary” HMTC; 25%) on the basis of germline 5% on theGiven significant biomarker and therapeutic potential, noncoding RNAs have been the focus of major research efforts Our laboratory has previously reported significant differential miRNA expression between SMTC and HMTC The suggestion of a therapeutic mechanism based on miRNA regulation of autophagy (a ubiquitous process of cellular subsistence) has also been raised in our prior studies, and this is a theme that has subsequently gained further research interest under the banner of “oncophagy” Despite the innumerable and significant molecular advances that have occurred over the last three decades, improved survival outcomes for patients with MTC (and sporadic disease in particular) have not occurred Ethical approval for all studies was granted by the Human Research Ethics Committees of the Northern Sydney Central Coast Area Health Service, the Alfred Hospital and the University of Sydney. Methods are detailed in P < 0.01) and in MZ-CRC-1 90% cell viability was evident (P = 0.03). When comparing cell lines, the pre-miR-9-3p effect was significantly greater in the TT cell line (P < 0.01).MTS assays performed at 48 h post transfection of pre-miR-9-3p or negative control demonstrated a significant impact on cell viability in both TT and MZ-CRC-1 cell lines. Mean TT cell viability (vs. negative control) was 77% (P = 0.018), whereas MZ-CRC-1 cell colonies were reduced by 26% (P = 0.016).Additional clonogenic assays were performed to further explore the pre-miR-9-3p effect on cell viability. FigureP < 0.01) and higher G2 (P < 0.01) cell phase counts when compared to negative control. More specifically, the G1 cell population was reduced by 4.67% and the G2 population increased by 4.12%. This effect was not apparent in the MZ cell line, however. Of note was the absence of a significant increase in the sub-G1 population of cells in both cell lines following miR-9-3p transfection.After demonstration of an effect upon cell proliferation, the mechanism of this effect was explored. P = 0.02). In addition, this figure demonstrates significant increases in autophagy markers, Atg5 and LC3BII (P < 0.01) following pharmacological induction with rapamycin (compared to 3-MA blockade). These results served as controls for post-miR-9-3p transfection immunoblots on both cell lines.Prior to examining the impact of miRNAs upon autophagy and apoptosis pathways specifically, pharmacological induction (Rapamycin) and blockade  of autophagy were imposed. Subsequent miR-9-3p transfected lysates from both cell lines resulted in evidence of a significant reduction in markers of autophagic flux . More specifically, BCL2 was suppressed in TT cells significantly (P = 0.014) but not MZ-CRC-1 cells (P = 0.083). LAMP1 was downregulated in both cell lines significantly  and MTOR was not significantly suppressed in either cell line .Following array studies, P < 0.01), consistent with targeted Atg5 inhibition. This effect was not seen, however, in the MZ-CRC-1 cell line, where subtle differences between negative control and miR-9-3p transfection were not significant (P = 0.23).In order to test the hypothesis of miR-9-3p-targeted suppression of Atg5, a luciferase reporter assay was constructed and performed in both cell lines. This involved transient vector transfection and measurement of firefly and renilla activity. FigureP = 0.04) and 2% , respectively. In keeping with the lack of elevated cPARP expression in the MZ-CRC-1 cell line, Atg5 knockdown did not influence cellular proliferation when compared to negative control transfection.Additional Atg5 siRNA knockdown resulted in significantly reduced Atg5 protein expression in association with markedly elevated cleaved PARP, but only in the TT cell line (results not shown). Atg5 knockdown also led to reduced cellular proliferation, but not to the same extent as seen following miR-9-3p transfection with an observed reduction in the number of viable cells by 12.6% .To further investigate the role of miR-9-3p regulation of autophagy, cell lines were treated with an autophagy inducer (Rapamycin) or a known autophagy blocker (Chloroquine) for 48 h. Using qPCR, significant differences were observed in miR-9-3p expression between treatments in both cell lines. More specifically, miR-9-3p expression was significantly higher after treatment with Rapamycin when compared to Chloroquine  and sporadic (n = 6) cases of MTC were investigated using a customized TLDA gene array card (as previously described for in vitro studies). P < 0.1).Differences between hereditary (n = 8) and sporadic (n = 18) cases of disease with the genes of interest being PIK3C3 (on the basis of the autophagy array data) and Beclin-1, which was selected given previously demonstrated importance in other cancer types. Selected autophagy gene mRNA expression results are presented in FigurePIK3C3 mRNA expression was not supported by validation experiments (P = 0.8). Beclin-1 expression, however, was shown to be elevated in both HMTC and SMTC , with sporadic cases of disease possessing significantly higher expression when compared to hereditary .Validation studies involved comparison of hereditary . Fifty-three percent and 47% of patients were found to have positive central and lateral compartment nodal metastases, respectively, at the index resection. Five patients were found to be positive for germline RET gene mutations consistent with a diagnosis of HMTC.The median age of patients at diagnosis was 55 years and 58% were female. Thyroid nodule investigation was the most common presentation (79%), although two patients were identified following familial Over a median follow-up time of 59 months, 79% went on to suffer from residual disease . Distant metastases were diagnosed in 47% and mortality was observed in 26%.Beclin-1 expression correlations with a variety of clinicopathological outcome indices. Associations between Beclin-1 expression and tumor size, extra-thyroidal extension or nodal metastases at diagnosis were not proven. However, with regard to clinical outcome, elevated Beclin-1 expression was significantly associated with the development of residual disease.RET gene mutation; a discovery that has primarily assisted those with hereditary disease. There remains a need to further interrogate alternative strategies and novel mechanisms, particularly for those with sporadic disease. These studies have revealed further insights into the role of miRNA regulation of autophagy within the context of sporadic disease in particular.MTC is a disease that has long been defined by the Following prior studies RET gene mutations. It has recently been suggested that intratumoral heterogeneity may be a large factor in tumor adaptation and therapeutic response Differential findings between cell lines were a common theme throughout experimentation. This may reflect the origins and molecular characteristics of these two cell lines which specifically harbor different In keeping with this, a possible explanation for the greater therapeutic effect in the TT cell line relates to basal cell line miRNA expression. Preliminary findings (not shown in Results) showed that basal miR-9-3p expression was significantly higher in the MZ-CRC-1 cell line. While still engaging a therapeutic effect, it would appear that additional elevation of miR-9-3p in the cell line had a finite influence, and represented a relatively lower level of increased expression . In contrast, the low miR-9-3p expression seen in the TT cell line resulted in a greater relative change in miRNA expression following transfection that was subsequently associated with a larger therapeutic effect. This suggestion highlights the potential kinetics of miRNA regulation, in that changes in relative expression, rather than absolute expression, are a key regulatory determinant.The mechanism of the miR-9-3p effect was investigated initially with cell cycle analysis. While significant G2 arrest was observed in the TT cell line, the change was relatively subtle, and this effect was absent in the MZ-CRC-1 cell line. Additionally, populations of sub-G1 cells, in either cell line, were not significantly altered by miR-9-3p transfection. Typically, a therapeutic effect (and particularly with G2 arrest) is accompanied by a large proportion of cells in apoptosis This is of interest given subsequent results delineating cleaved PARP immunoblotting expression. In both cell lines, following miR-9-3p transfection, cPARP expression was significantly elevated, providing more specific evidence of cell death via apoptosis. It could be assumed that miR-9-3p was enacting a mechanism based on cell death via apoptosis. However, these results were observed in parallel with suppression of markers of autophagy in both cell lines., and in MTC specifically. Our previous studies had identified a suggestive change in autophagic flux following knockdown of miR-183 in the TT cell line This raises a number of issues. Firstly, these findings are novel in identification of miR-9-3p regulation of autophagic flux in vitroSecondly, the targeted influence of miR-9-3p was able to be isolated. More specifically, the only predicted target of miR-9-3p within the context of autophagy, Atg5, was shown through luciferase reporter experimentation to be a validated target (in the TT cell line). This has assisted in unlocking the precise mechanism of the miR-9-3p effect and identified an additional level of regulation that could be exploited therapeutically.Employing targeted siRNA Atg5 knockdown as an adjuvant therapeutic strategy has been explored once previously in MTC. Lin et al. examined the in vitro impact of Atg5 suppression in combination with tyrosine kinase inhibitor (TKI) therapy and found that autophagy inhibition appeared to abrogate the therapeutic effect of TKI treatment Thirdly, experiments employing miR-9-3p and then also siRNA to Atg5 itself revealed not only autophagy inhibition, but evidence of crosstalk between autophagy and apoptosis pathways. This concept has been promoted by Xu et al., specifically within the context of miRNA BCL-2 and LAMP-1 to be significantly suppressed following miR-9-3p transfection, reinforcing the suggestion of miRNA-induced autophagy inhibition and also revealing potential key regulators. Validation of BCL-2 suppression is especially significant, given recent studies identifying antitumor activity through BCL-2 downregulated induction of apoptosis Further to miR-9-3p autophagy inhibition and crosstalk with apoptosis, array studies were confirmatory of this influence throughout a multitude of autophagy-related genes. Additional validation studies revealed BCL-2 to regulation of apoptosis and the complex interplay with autophagy has been recognized previously BCL2 may be the “single protein regulator” capable of regulating autophagy and apoptosis independently The importance of With regard to “autophagamiRs” Beclin-1 expression in SMTC. Additionally, expression correlated with clinical outcome; elevated expression identifying patients who developed residual disease.Lastly, when comparing clinical sporadic MTC tumors with hereditary cases, array studies revealed an almost universal elevation in autophagy-related genes in SMTC. Validation studies confirmed significantly elevated Beclin-1 have yielded conflicting results in a number of different cancer types Beclin-1 expression have compared cancer tissue with normal control tissue, as opposed to comparing two different groups within the same pool of cancers. It may be that MTC Beclin-1 expression is relatively underexpressed, in general, when compared to normal parafollicular C cells. The absence of “normal” parafollicular control tissue has been an ongoing issue in MTC research.Prognostic associations with Elevated Beclin-1 expression in sporadic tumors is suggestive of elevated basal autophagic flux. While there is no specific evidence presented here, it could be argued that autophagy is a tumor survival strategy, being engaged in times of cellular stress and ultimately resulting in a more aggressive disease phenotype. This is justified partly by this study, given in vitro evidence of autophagy inhibition resulting in cellular demise and additional primary tumor autophagy gene expression correlations with a worse clinical outcome. The concept of inducing autophagy inhibition in an adjuvant setting is gaining momentum and has recently been promoted in colon cancer Beclin-1, thyroid cancer, and MTC specifically. One recent study, however, has examined functional overexpression of Beclin-1 in thyroid cancer cell lines Beclin-1 sensitizes cells to treatment with proteasome inhibitors. Blockade of the ubiquitin–proteasome pathway would obviously be of future interest in treatment of sporadic MTC and is currently being employed clinically in refractory myeloma Little previous work has been undertaken with regard to Beclin-1 with BCL2 is also of interest and while Beclin-1 expression was examined in this study, it may be that its binding partner BCL2 may be the master regulator of this relationship BCL2 and this could be the future research focus.The known association of Beclin-1 expression may be a useful biomarker of development of residual disease and tumor overexpression has revealed an additional therapeutic option with the use of proteasome inhibitor therapy.In conclusion, autophagy is a tumor cell survival mechanism in MTC. Disabling of autophagy is of additional therapeutic advantage through crosstalk with apoptosis. None declared.


Chk1 forms a core component of the DNA damage response and small molecule inhibitors are currently being investigated in the clinic as cytotoxic chemotherapy potentiators. Recent evidence suggests that Chk1 inhibitors may demonstrate significant single agent activity in tumors with specific DNA repair defects, a constitutively activated DNA damage response or oncogene induced replicative stress.Growth inhibition induced by the small molecule Chk1 inhibitor V158411 was assessed in a panel of human leukemia and lymphoma cell lines and compared to cancer cell lines derived from solid tumors. The effects on cell cycle and DNA damage response markers were further evaluated.50 0.17 μM) compared to colon (2.8 μM) or lung (6.9 μM) cancer cell lines. Chk1 inhibition by V158411 in the leukemia and lymphoma cell lines induced DNA fragmentation and cell death that was both caspase dependent and independent, and prevented cells undergoing mitosis. An analysis of in vitro pharmacodynamic markers identified a dose dependent decrease in Chk1 and cyclin B1 protein levels and Cdc2 Thr15 phosphorylation along with a concomitant increase in H2AX phosphorylation at Ser139 following V158411 treatment.Leukemia and lymphoma cell lines were identified as particularly sensitive to the Chk1 inhibitor V158411 (mean GIThese data support the further evaluation of Chk1 inhibitors in hematopoietic cancers as single agents as well as in combination with standard of care cytotoxic drugs. The serine-threonine checkpoint kinases Chk1 and Chk2 form central key components in the DNA damage signaling response (DDR) . Despitein vitro. The cytotoxicity of AR678 was suggested to be due to inhibition of S-phase Chk1 and failure of cytotokinesis or induction of apoptotic death and sensitivity correlated with levels of endogenous DNA damage most likely induced by replicative stress [Evidence has begun to emerge that small molecule Chk1 inhibitors may have significant single agent activity in cancer cells with specific underlying genetic defects. This is often defined as a synthetic lethal relationship ,16. These stress .We utilized our own novel, potent, selective small molecule inhibitor of Chk1, V158411, to screen cell lines from a range of cancer types in an effort to identify additional tumor types for which single agent Chk1 inhibitor therapy may prove a rational treatment option.Emerging evidence suggests that inhibiting the checkpoint kinase Chk1, in addition to potentiating cytotoxic chemotherapeutic agents, may exhibit single agent activity in cancers with underlying DNA repair, DNA damage response or DNA replication defects. We used the highly selective, potent checkpoint kinase inhibitor V158411 as a tool to identify cancer types where checkpoint inhibition may be a rationale therapeutic option.in vitro with IC50s of 3.5 and 2.5 nM respectively [50 of 48 nM and Chk2 on Ser516 with an IC50 of 904 nM indicating a 19-fold cellular selectivity for Chk1 over Chk2. V158411 potentiated cytotoxic chemotherapy in p53 defective cancer cells in vitro and in vivo.V158411 is a novel, potent, selective inhibitor of recombinant Chk1 and Chk2 kinases ectively . Against50 of 0.17 μM . There was no correlation between pChk1 (S345) expression levels and sensitivity to V158411 . In three of the Chk1 inhibitor sensitive leukemia/lymphoma cell lines, U937, HL-60 and MV4-11, the endogenous levels of H2AX phosphorylated on Ser139 was much higher compared to all other cell lines. Across the whole panel of cell lines analyzed, there was a weak correlation (R2 = 0.404) between pH2AX (S139) expression and V158411 sensitivity but no correlation (R2 = 0.250) when just the leukemia and lymphoma subset of cell lines were analyzed  but overall, the blood-derived cancer lines  were not dramatically more sensitive to Chk1-A than those derived from solid tumors . This is in contrast to that observed with V158411, a novel Chk1 inhibitor structurally distinct from Chk1-A. Hematopoietic-derived cell lines  were around 28-fold more sensitive to V158411 compared to cell lines derived from solid cancers . As observed in our study, Chk1-A induced a collapse of DNA replication and apoptosis without premature mitosis in the HEL92.1.7 human erythroleukemia cell line [et al. is applicable to a wider range of blood-derived cancers. The observation that Chk1-A exhibits potent single agent activity in solid cancer cell lines as well as hematopoietic cancer cell lines (in contrast to V158411 and PF-477736) suggests that Chk1-A may inhibit additional kinases important for proliferation and survival of solid cancer-derived cell lines.Previous work by Davies et al.  identifiThe mechanism by which Chk1 inhibition leads to the death of hematopoietic cells is yet to be fully elucidated and understood. The molecular defects in these cell lines most likely occur in pathways for which Chk1 can mutually compensate to protect genomic integrity and therefore Chk1 inhibition is synthetically lethal. Studies in other cancer models provide possible mechanisms which may leave these cell lines more Chk1 dependent than other solid cancer cell types such as lung or colon cancer. Two possible mechanisms have so far been suggested for Chk1 inhibitor sensitivity: increased oncogenic replicative stress or reduced DNA repair capacity due to defects in specific DNA repair pathways especially those responsible for processing and repairing DNA double strand breaks (DSBs) ,30.Myc oncogene as a potential underlying mechanism for sensitivity to Chk1 inhibition. In the Eμ-myc lymphoma model, sensitivity to the Chk1 inhibitor PF-477736 was dependent on a p53 wild type background. Apoptosis induced by oncogenic replicative stress can be suppressed by ATR and Chk1 [Two previous studies, one in neuroblastoma cells  and anotand Chk1 ,31. All and Chk1 ,33 and tand Chk1  may undec-Myc oncogene, the FLT3-ITD mutation induces oncogenic replicative stress [MV4-11 cells harbor an internal tandem duplication (ITD) in the juxtamembrane domain of FLT3 leading to deregulated FLT3 kinase signaling that drives the proliferation of this cell line . Like dee stress ,37 and me stress  and in MMolecular defects in pathways responsible for processing DNA breaks, especially DNA double strand breaks, have been postulated to be potentially synthetically lethal with Chk1 inhibition. One example so far discovered is in the Fanconi Anemia (FA) DNA repair pathway. The Fanconi Anemia (FA) repair pathway is responsible for repairing crosslinked DNA and maintaining chromosomal stability . FA defiin situ. Replicative stress due to deregulated oncogenes, and hence sensitivity to Chk1 inhibitors, may be amplified due to selection of cells that proliferate rapidly in culture and may not truly reflect the oncogenic replicative stress observed in human disease. Further work is needed on leukemia and lymphoma samples derived from patients that have undergone limited ex vivo culture to confirm and understand these observations.All the studies so far conducted have been undertaken on established cell lines that grow indefinitely under optimal culture conditions. Selection of these cell lines for growth in culture may have resulted in the selection for factors that drive cell proliferation in culture rather than tumor proliferation From these studies, Chk1 inhibitors may be a useful addition to the arsenal of drugs suitable for use in the clinic against hematopoietic cancers. The ability to stratify patients based on genetic markers predictive of sensitivity will be necessary to achieve optimal clinical benefit. Studies so far suggest that deregulated Myc oncogene expression may be one such marker.Cell lines derived from human leukemias and lymphomas exhibited greater sensitive to the Chk1 inhibitor V158411 than cell lines derived from solid tumors. Replication stress, due to oncogene activation, may account for the sensitivity of these cell lines to Chk1 inhibition. This data supports the further evaluation of Chk1 inhibitors in hematopoietic cancers as single agents as well as in combination with standard of care cytotoxic drugs.All cells were obtained from the American Type Culture Collection (ATCC) or Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures (DSMZ) and cultured in DMEM or RPMI containing 10% FCS (Invitrogen). The cytotoxicity of V158411 was determined following exposure of cells in 96 well plates to a 10-point titration for 72 hours. Cell proliferation was determined using sulphorhodamine B staining following protein precipitation with 10% TCA for adherent cell lines or cell titer glo (Promega) for suspension cell lines. For cell counts, cells were seeded in 24 well plates and counted daily using a haemocytometer following trypan blue staining. Cells were diluted to maintain log phase cultures.50 of V158411 for 24 or 48 hours. Caspase-3/7 activity was determined using a homogenous caspase-3/7 luminescence kit (Promega).Cells were seeded in 96 well plates and treated with 5- or 10-times the GIAnti- pHistone H3 (S10) was obtained from Millipore; Chk1, pChk1 (S317), pChk1 (S345), Cdc2, pCdc2 (Y15), Cyclin B1 and pH2AX (S139) from Cell Signaling Technologies and pChk1 (S296) from Abcam. Treated and untreated cells were washed once with PBS and lysed in 50 mM Tris-pH6.8, 2% SDS, protease and phosphatase inhibitor cocktails (Roche) and boiled for 5 minutes. Protein concentration was determined using BCA kit (Pierce). Equal amounts of lysate were separated by SDS-PAGE and western blot analysis conducted using the antibodies indicated above.Cells were seeded in 6-well plates and subsequently treated with the indicated concentrations of V158411 for 24 or 48 hours. All cells were harvested, fixed in 70% ethanol and stained with propidium iodide/RNase A. Cell cycle profiles were examined by flow cytometry using a FACSArray cytometer (BD) and FACSDiva software (BD).CB, KS and AJM undertook this work as employees of Vernalis R&D Ltd. AJM is a stock option holder of Vernalis R&D Ltd.AJM designed and coordinated the studies and is the author responsible for writing the paper. CB, KS and AJM carried out the studies. All authors read and approved the final manuscript.All authors are either current or past employees of Vernalis R&D Ltd and undertook this study as part of their employment. AJM is a stock option holder of Vernalis R&D Ltd.


Cancer cell lines have a prominent role in the initial stages of drug discovery, facilitating high-throughput screening of potential drugs. However, their clinical relevance remains controversial.We assess whether drug sensitivity in cancer cell lines is able to discriminate tissue specificity. We find that cancer-specific drugs do not show higher efficacies in cell lines representing the respective tissues. Even when considering distinct cancer subtypes and targeted therapies, most drugs are evenly effective/ineffective throughout all cell lines.To get the most out of cell line panels, it will be necessary to look into their molecular characteristics, and integrate them into systems biology frameworks.The online version of this article (doi:10.1186/s12943-015-0312-6) contains supplementary material, which is available to authorized users. Apart f biology ,3, cancel trials ,5.However, despite their fundamental role in biomedical research, the clinical relevance of cell lines remains highly controversial ,7. ApartGiven the intrinsic heterogeneity of most cancers , no indiSimilarly, we investigated whether intended drug targets are expressed in the corresponding cell lines and, if so, whether the drug is active in this cell line, exploiting proteomics data of NCI-60 . Again, Although alternative models for drug screening and development are generated , cancer


The phosphopeptides were further filtered with Ascore system and 1,340 phosphoprotein groups, 2,760 unique phosphopeptides, and 4,549 unique phosphosites were identified. Our study suggested that differentially phosphorylated Cdk5, PML, AP-1, and HSF-1 might work together to promote vimentin induced epithelial to mesenchymal transition (EMT) in the drug resistant cells. EGFR and HGF were also shown to be involved in this process.Because of the absence of a clear therapeutic target for triple negative breast cancer (TNBC), conventional chemotherapy is the only available systemic treatment option for these patients. Despite chemotherapy treatment, TNBC patients still have worse prognosis when compared with other breast cancer patients. The study is to investigate unique phosphorylated proteins expressed in chemoresistant TNBC cell lines. In the current study, twelve TNBC cell lines were subjected to drug sensitivity assays against chemotherapy drugs docetaxel, doxorubicin, gemcitabine, and cisplatin. Based on their half maximal inhibitory concentrations, four resistant and two sensitive cell lines were selected for further analysis. The phosphopeptides from these cells were enriched with TiO Breast cancer is the most common cancer in women . Althougβ and AP-1 transcription factors might be involved in the tamoxifen resistance in MCF-7 cells [In the last two decades, proteomics has emerged as a powerful tool in biomarker discovery and mechanism understanding. Using these tools, researchers can efficiently perform large-scale screening to attain valuable information. Proteomics has been used as a tool to identify new disease related biomarkers in TNBC , 12. Pro-7 cells . Rexer e-7 cells . Olivera-7 cells . HoweverFor the purpose of this study, TNBC cell lines responding to multiple chemotherapeutic drugs were studied and were compared. Twelve established TNBC cell lines were tested against four chemodrugs and the half maximal inhibitory concentrations (IC50s) were calculated. The phosphorylated peptides of four resistant and two sensitive cell lines were analyzed using LC-MS/MS to discover important pathways related to chemodrug resistance of TNBC. Our study may lead to identification of useful prognostic biomarkers and therapeutic pathways for TNBC treatment.μg/mL streptomycin, at 37°C in 5% CO2.Triple negative breast cancer cell lines MDA-MB-231, MDA-MB-468, MDA-MB-436, HCC1187, HCC1806, and HCC1937  were obtained from American Tissue Type Culture Collection  , 23. CelCell lines were treated with docetaxel, doxorubicin, gemcitabine, and cisplatin in vitro to determine the half maximal inhibitory concentration (IC50) of each drug. The cells were treated with DMSO or twenty predetermined doses of each drug for two days. Cell viabilities were determined by CellTiter-Glo Luminescent Cell Viability Assay . Triplicated experiments were performed twice and the IC50s were calculated using GraphPad Prism 5 software.μL of 1 M DTT (Thermo Fisher Scientific) was added to samples containing 1 mg of proteins and incubated at 56°C for 1 hour and followed by an incubation at room temperature for 40 min in darkness with 80 μL of 1 M IAA added into the buffer. Each sample was treated with 0.11 volumes of ice-cold 100% trichloroacetic acid (TCA)  on ice for 10 min and 500 μL of ice-cold 10% TCA on ice for 20 min and then was spun down at 20,000 ×g for 30 min. The pellet was washed with 500 μL of acetone and was centrifuged again at 20,000 ×g for 10 min. The protein pellets of all samples were collected and dried in a vacuum evaporator. 500 μL of 100 mM ammonium bicarbonate (Sigma Aldrich) and 20 μg of trypsin  were added to the sample in each tube at 37°C for 2 hours. An additional 20 μg of trypsin was added to the sample and subsequently incubated for 16 hours. The peptides were then filtered through 10 kDa filter columns  and dried via vacuum evaporator.Cultured cells were lysed in lysing buffer  and the supernatant was collected into 1.5 mL tubes. Protein concentration of the lysate was determined using the Pierce BCA protein assay (Thermo Fisher Scientific). 20 μL of loading buffer (80% acetonitrile (ACN) and 2% trifluoroacetic acid (TFA)) was added to 1 mg of peptides. The mixture was incubated with 4 mg of TiO2 beads  for 1 hour. The samples were centrifuged at 3,000 ×g for 5 min and the supernatant was discarded. TiO2 beads were collected and washed with 1 mL wash buffer I  followed by 1 mL of wash buffer II , each for 20 min at 4°C with rotation and centrifuged at 3,000 ×g for 5 min. The phosphopeptides were eluted first with 400 μL elution buffer I  and was followed by 400 μL elution buffer II . Nest Group MicroSpin strong cation exchange solid phase extraction tubes  were used as a separation technique before mass spectrometry to reduce the complexity of samples and enhance the identification rate.400  m/z 400) and ten MS/MS experiments at low resolution on the linear trap while the full scan was completed. For CID the intensity threshold was set to 5000 and the mass range was 350–2000.All peptide fractions were desalted before analysis using C18 tips made from the Empore C18 90 mm Disk . Nanoliquid chromatography and tandem mass spectrometry (nLC-MS/MS) with Collision Induced Dissociation (CID) was performed on a LTQ-Orbitrap (Thermo Fisher Scientific) integrated with an Eksigent nano-LC . The flow rate for reverse-phase chromatography was 500 nL/min for the loading and analytical separation . Peptides were resolved by the gradient of 3–40% buffer B over 180 min. The Orbitrap was operated in data-dependent mode with a full precursor scan at high-resolution (60000 athttp://www.thegpm.org/tandem/) algorithms, while running a target decoy search strategy to increase protein identity confidence. Mascot and Sequest were searched with a fragment ion mass tolerance of 0.80 Da and a parent ion tolerance of 10.0 PPM and tolerated up to two missed trypsin cleavages. Carbamidomethylation of Cysteine was specified as a fixed modification. Glu or Gln to pyro-Glu of the n-terminus, oxidation of methionine, and phosphorylation of serine, threonine, and tyrosine were specified as variable modifications.Mass spectra were searched against the Uniprot Human database using Proteome Discoverer software , utilizing the Sequest (Thermo Fisher Scientific), Mascot , and X! Tandem  to quantify and validate the MS/MS peptide and protein identifications. Identifications were accepted if they had a greater than 95% peptide probability and contained at least one identifiable phosphopeptide. Scaffold PTM  was used to annotate phosphosites located in MS/MS spectra. Phosphosite localization probabilities were calculated using the Ascore probability based scoring technique  and onlyt-test of each peptide between the groups of the three comparisons was performed and the peptides with P values < 0.05 and a fold change of at least 2.0 (≧2.0 or ≦0.5) were considered differential peptides. From the comparison (1), all changed phosphopeptides were further analyzed using online database String which is a database of known and predicted protein interactions including direct  and indirect  associations [The spectral count data of the phosphopeptides were acquired through Scaffold PTM and were compared between grouped cell lines: (1) all four resistant cell lines were compared with the two sensitive cell lines HCC1806 and MDA-MB-468; (2) resistant cell lines MDA231 and MDA-MB-436 were compared to the two sensitive cell lines; (3) resistant cell lines HCC1187 and HCC1937 were compared to the two sensitive cell lines. A ciations .P values less than 0.05 were imported to Permutmatrix software [Hierarchical clustering analysis was performed using Euclidean distance formulation and complete linkage criteria for linkage of normalized phosphopeptide spectrum counts. Based on the comparison (1), only the peptide spectrum counts with software .R2 values of the drug sensitivity curves (data not shown) less than 0.7 were also considered as no response. HCC1187, MDA-MB-436, MDA-MB-231, and HCC1937 had the highest IC50s for at least three of the four drugs and were thus considered chemotherapy-resistant. HCC1806 and MDA-MB-468 were ranked lowest on the IC50 scale for at least three of the four drugs and were considered chemotherapy-sensitive. These six cell lines were selected for phosphorylated protein analysis.Protein phosphorylation is an important posttranslational modification that governs many of the signaling changes in cancer cells. The current study was performed to screen the signaling pathway changes, through the comparison of phosphorylated proteins in TNBC cell lines with extreme responses to the four chemotherapy drugs. The half maximal inhibitory concentrations (IC50s) of twelve TNBC cell lines against four chemotherapy drugs were determined and four resistant and two sensitive cell lines were selected for further analysis. Cell lines were ranked according to their IC50s against each drug . No resphttp://dx.doi.org/10.1155/2014/390781). Instances where the same peptide sequence had different phosphosites were counted as one peptide and ultimately 3,062 peptide sequences were identified  against the Uniprot-Human database with the application of a decoy database. Proteome Discoverer was used in tandem with Scaffold and Scaffold PTM for quantification. A total of 1,645 phosphoprotein groups were identified by scaffold software across all six TNBC cell lines, using peptide probability thresholds of 95% with a minimum of one unique peptide . The pepentified . The oveentified . When thentified .  FigureP value and fold change between the two groups of cell lines. Only phosphopeptides with a P value less than 0.05 and a fold change above 2 or less than 0.5 were considered. From three sets of comparisons . The mass spectra quantification data of these phosphopeptides were exported and further analyzed to determine the variations between chemotherapy-resistant and chemotherapy-sensitive cell lines (Supplementary Table  2). The spectrum counts of phosphorylated peptides were evaluated by computing the  seen in , three sFour drug resistant cell lines and two drug sensitive cell lines selected by IC50 ranking were subjected to phosphoproteome analysis in the current study. To confirm that these cell lines can be separated by the differentially expressed phosphopeptides into two groups: chemotherapy-resistant and chemotherapy-sensitive TNBC, the clustering analysis was performed. Over the last few decades there has been a steady decrease in breast cancer mortality rate largely due to the improvements in the treatment of breast cancer . DespiteLabel-free quantification was favored in this study since it has the largest dynamic range and highest proteome coverage-a prerequisite for the objective of this study as protein phosphorylation is a transient process and can be found with varying concentrations , 32. FraBecause different phosphosites in a protein may trigger either protein activation or inactivation, we used phosphosite instead of phosphoprotein as unit for quantification. The functions of proteins will be discussed according to the changes of phosphosites. Among the dramatically altered phosphoproteins identified in the current study, many have also been reported to be important in tumor progression and/or drug resistance. Our results further support the roles of these proteins in TNBC drug resistance and offer new insights for future studies. Some new phosphorylated sites found in this study together with several of the previously reported protein phosphosites were connected for the first time to TNBC drug resistance. The important signaling changes are discussed below.Transcription factor AP-1 (AP-1) is a multiprotein transcription factor and a member of the Jun and Fos protoontogenetic family. Previous studies have linked the activated AP-1 and its family members to increased tumorigenesis, metastasis, and invasion , 34 as wHeat Shock Factor 1 (HSF-1) is a master regulator for the transcription and heat shock proteins (HSPs) and was reported to induce a multidrug resistance phenotype through constitutive activation of the multidrug resistance gene 1 (MDR-1) . In the It has been reported that epidermal growth factor receptor (EGFR) plays a significant role in hepatocyte growth factor receptor (HGF/c-Met) mediated biological activities . ActivatIt is noticeable that many of the changed phosphoproteins found in the current study were involved in mRNA processing including heterogeneous nuclear ribonucleoprotein A2/B1, serine/arginine repetitive matrix 1 and matrix 2, eukaryotic translation initiation factor 4 gamma-1, and several others. As reviewed by Eblen, alternative splicing is a normal cellular process that can be manipulated by a cancer cell to enhance survival in response to chemotherapeutic treatment . We alsoThe current study has shown that proteomic analysis is a powerful tool for profiling of the phosphorylation patterns and may help better understand drug resistant TNBC cells. Our data suggested that PML, AP-1, and HSF-1 were preferentially activated in resistant TNBC cells and might promote downstream signals including vimentin activation. In addition, our study also suggested that Cdk5 might also promote vimentin and LMNB1 activation leading to an increased EMT in the resistant TNBC cells. We are also reporting on the potential roles of EGFR and HGF in the promotion of a multiple drug resistance (MDR) phenotype in TNBC. We have identified several signaling pathways that may work together to mediate the drug resistance in TNBC .Supplementary materials contain three Excel files with additional peptide data generated during this study. Table 1, total peptide and phosphosite list generated by Scaffold. Table 2, peptide quatification. Table 3, fold change data.