48 research outputs found

    Different mechanisms for resistance to trastuzumab versus lapatinib in HER2- positive breast cancers -- role of estrogen receptor and HER2 reactivation

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    Introduction: The human epidermal growth factor receptor 2 (HER2)-targeted therapies trastuzumab (T) and lapatinib (L) show high efficacy in patients with HER2-positive breast cancer, but resistance is prevalent. Here we investigate resistance mechanisms to each drug alone, or to their combination using a large panel of HER2-positive cell lines made resistant to these drugs. Methods: Response to L + T treatment was characterized in a panel of 13 HER2-positive cell lines to identify lines that were de novo resistant. Acquired resistant lines were then established by long-term exposure to increasing drug concentrations. Levels and activity of HER2 and estrogen receptor (ER) pathways were determined by qRT-PCR, immunohistochemistry, and immunoblotting assays. Cell growth, proliferation, and apoptosis in parental cells and resistant derivatives were assessed in response to inhibition of HER or ER pathways, either pharmacologically (L, T, L + T, or fulvestrant) or by using siRNAs. Efficacy of combined endocrine and anti-HER2 therapies was studied in vivo using UACC-812 xenografts. Results: ER or its downstream products increased in four out of the five ER+/HER2+ lines, and was evident in one of the two intrinsically resistant lines. In UACC-812 and BT474 parental and resistant derivatives, HER2 inhibition by T reactivated HER network activity to promote resistance. T-resistant lines remained sensitive to HER2 inhibition by either L or HER2 siRNA. With more complete HER2 blockade, resistance to L-containing regimens required the activation of a redundant survival pathway, ER, which was up-regulated and promoted survival via various Bcl2 family members. These L-and L + T-resistant lines were responsive to fulvestrant and to ER siRNA. However, after prolonged treatment with L, but not L + T, BT474 cells switched from depending on ER as a survival pathway, to relying again on the HER network (increased HER2, HER3, and receptor ligands) to overcome L's effects. The combination of endocrine and L + T HER2-targeted therapies achieved complete tumor regression and prevented development of resistance in UACC-812 xenografts. Conclusions: Combined L + T treatment provides a more complete and stable inhibition of the HER network. With sustained HER2 inhibition, ER functions as a key escape/survival pathway in ER-positive/HER2-positive cells. Complete blockade of the HER network, together with ER inhibition, may provide optimal therapy in selected patients

    Species-Specific Activity of SIV Nef and HIV-1 Vpu in Overcoming Restriction by Tetherin/BST2

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    Tetherin, also known as BST2, CD317 or HM1.24, was recently identified as an interferon-inducible host–cell factor that interferes with the detachment of virus particles from infected cells. HIV-1 overcomes this restriction by expressing an accessory protein, Vpu, which counteracts tetherin. Since lentiviruses of the SIVsmm/mac/HIV-2 lineage do not have a vpu gene, this activity has likely been assumed by other viral gene products. We found that deletion of the SIVmac239 nef gene significantly impaired virus release in cells expressing rhesus macaque tetherin. Virus release could be restored by expressing Nef in trans. However, Nef was unable to facilitate virus release in the presence of human tetherin. Conversely, Vpu enhanced virus release in the presence of human tetherin, but not in the presence of rhesus tetherin. In accordance with the species-specificity of Nef in mediating virus release, SIV Nef downregulated cell-surface expression of rhesus tetherin, but did not downregulate human tetherin. The specificity of SIV Nef for rhesus tetherin mapped to four amino acids in the cytoplasmic domain of the molecule that are missing from human tetherin, whereas the specificity of Vpu for human tetherin mapped to amino acid differences in the transmembrane domain. Nef alleles of SIVsmm, HIV-2 and HIV-1 were also able to rescue virus release in the presence of both rhesus macaque and sooty mangabey tetherin, but were generally ineffective against human tetherin. Thus, the ability of Nef to antagonize tetherin from these Old World primates appears to be conserved among the primate lentiviruses. These results identify Nef as the viral gene product of SIV that opposes restriction by tetherin in rhesus macaques and sooty mangabeys, and reveal species-specificity in the activities of both Nef and Vpu in overcoming tetherin in their respective hosts

    Does proactive personality matter in leadership transitions? Effects of proactive personality on new leader identification and responses to new leaders and their change agendas

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    Despite the growing frequency of leadership transitions and their significant impact on team and organizational performance, little research has examined why and how teams develop an identification with a new leader or their subsequent receptiveness to the new leader’s change initiatives. Drawing from the contrast and congruence effects and the theoretical perspectives of leader identification, this study empirically tests a model in which the congruence of new leaders’ and their teams’ proactive personalities foster new leader identification, as well as the team’s behavioral responses to the new leader’s change agenda. This effect is strongest when the new leader’s proactive personality is higher than that of the former leader’s proactive personality (positive contrast). Our findings of a four-wave “before-and-after” transition survey of 155 hotel employees and 51 new leaders, achieved through polynomial regression analyses, proved very insightful. Essentially, we found that the congruence between a new leader’s and his/her team’s proactive personalities and the positive contrast between a former leader’s and the new leader’s proactive personalities enhanced new leader identification and the team’s shared identification with the new leader’s change agenda, and, thereby led the team to exhibit more behavioral engagement with, and voice behavior about, the new leader’s change agenda

    Developing risk prediction models for type 2 diabetes: a systematic review of methodology and reporting

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    <p>Abstract</p> <p>Background</p> <p>The World Health Organisation estimates that by 2030 there will be approximately 350 million people with type 2 diabetes. Associated with renal complications, heart disease, stroke and peripheral vascular disease, early identification of patients with undiagnosed type 2 diabetes or those at an increased risk of developing type 2 diabetes is an important challenge. We sought to systematically review and critically assess the conduct and reporting of methods used to develop risk prediction models for predicting the risk of having undiagnosed (prevalent) or future risk of developing (incident) type 2 diabetes in adults.</p> <p>Methods</p> <p>We conducted a systematic search of PubMed and EMBASE databases to identify studies published before May 2011 that describe the development of models combining two or more variables to predict the risk of prevalent or incident type 2 diabetes. We extracted key information that describes aspects of developing a prediction model including study design, sample size and number of events, outcome definition, risk predictor selection and coding, missing data, model-building strategies and aspects of performance.</p> <p>Results</p> <p>Thirty-nine studies comprising 43 risk prediction models were included. Seventeen studies (44%) reported the development of models to predict incident type 2 diabetes, whilst 15 studies (38%) described the derivation of models to predict prevalent type 2 diabetes. In nine studies (23%), the number of events per variable was less than ten, whilst in fourteen studies there was insufficient information reported for this measure to be calculated. The number of candidate risk predictors ranged from four to sixty-four, and in seven studies it was unclear how many risk predictors were considered. A method, not recommended to select risk predictors for inclusion in the multivariate model, using statistical significance from univariate screening was carried out in eight studies (21%), whilst the selection procedure was unclear in ten studies (26%). Twenty-one risk prediction models (49%) were developed by categorising all continuous risk predictors. The treatment and handling of missing data were not reported in 16 studies (41%).</p> <p>Conclusions</p> <p>We found widespread use of poor methods that could jeopardise model development, including univariate pre-screening of variables, categorisation of continuous risk predictors and poor handling of missing data. The use of poor methods affects the reliability of the prediction model and ultimately compromises the accuracy of the probability estimates of having undiagnosed type 2 diabetes or the predicted risk of developing type 2 diabetes. In addition, many studies were characterised by a generally poor level of reporting, with many key details to objectively judge the usefulness of the models often omitted.</p

    Large expert-curated database for benchmarking document similarity detection in biomedical literature search

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    Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

    Ablation of CRTAC1 inhibits post-traumatic OA in female mice.

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    <p><b>A</b>, Safranin-O/fast green stain of knee articular cartilage of wild type and <i>Crtac1</i><sup><i>-/-</i></sup> female mice 16 weeks after DMM surgery showing decreased structural destruction of articular cartilage after deletion of <i>Crtac1</i>. <b>B</b>, The maximum and summed OA histologic scores for articular cartilage 16 weeks after DMM surgery in wild type and <i>Crtac1</i><sup><i>-/-</i></sup> female mice. <b>C</b>, Safranin-O/fast green stain of right knee joints showing that ablation of <i>Crtac1</i> reduce osteophyte formation at the margin of articular cartilage (arrows) 16 weeks after DMM surgery. <b>D</b>, Maximum and summed histologic scores of osteophytes in wild type and <i>Crtac1</i><sup><i>-/-</i></sup> female mice 16 weeks after DMM surgery. Scale bars: 200 μm (A), 400 μm (C). All data are means ± SDs. Nonparametric Mann-Whitney tests were performed.</p
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