61 research outputs found

    Table_1_Nomogram predicting overall survival after surgical resection for retroperitoneal leiomyosarcoma patients.docx

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    BackgroundSurgery is the best way to cure the retroperitoneal leiomyosarcoma (RLMS), and there is currently no prediction model on RLMS after surgical resection. The objective of this study was to develop a nomogram to predict the overall survival (OS) of patients with RLMS after surgical resection.MethodsPatients who underwent surgical resection from September 2010 to December 2020 were included. The nomogram was constructed based on the COX regression model, and the discrimination was assessed using the concordance index. The predicted OS and actual OS were evaluated with the assistance of calibration plots.Results118 patients were included. The median OS for all patients was 47.8 (95% confidence interval (CI), 35.9-59.7) months. Most tumor were completely resected (n=106, 89.8%). The proportions of French National Federation of Comprehensive Cancer Centres (FNCLCC) classification were equal as grade 1, grade 2, and grade 3 (31.4%, 30.5%, and 38.1%, respectively). The tumor diameter of 73.7% (n=85) patients was greater than 5 cm, the lesions of 23.7% (n=28) were multifocal, and 55.1% (n=65) patients had more than one organ resected. The OS nomogram was constructed based on the number of resected organs, tumor diameter, FNCLCC grade, and multifocal lesions. The concordance index of the nomogram was 0.779 (95% CI, 0.659-0.898), the predicted OS and actual OS were in good fitness in calibration curves.ConclusionThe nomogram prediction model established in this study is helpful for postoperative consultation and the selection of patients for clinical trial enrollment.</p

    TiO<sub>2</sub> with Tandem Fractionation (TAFT): An Approach for Rapid, Deep, Reproducible, and High-Throughput Phosphoproteome Analysis

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    Mass-spectrometry-based phosphoproteomic workflows traditionally require efficient prefractionation and enrichment of phosphopeptides to gain an in-depth, global, and unbiased systematic investigation of phosphoproteome. Here we present TiO<sub>2</sub> with tandem fractionation (TAFT) approach, which combines titanium dioxide (TiO<sub>2</sub>) enrichment and tandem high-pH reverse-phase (HpRP) for phosphoproteome analysis in a high-throughput manner; the entire workflow takes only 3 h to complete without laborious phosphopeptide preparation. We applied this approach to HeLa and HepG2.2.15 cells to characterize the capability of TAFT approach, which enables deep identification and quantification of more than 14 000 unique phosphopeptides in a single sample from 1 mg of protein as starting materials in <4 h of MS measurement. In total, we identified and quantified 21 281 phosphosites in two cell lines with >91% selectivity and high quantitative reproducibility (average Pearson correlation is 0.90 between biological replicates). More generally, the presented approach enables rapid, deep, and reproducible phosphoproteome analysis in a high-throughput manner with low cost, which should facilitate our understanding of signaling networks in a wide range of biological systems or the process of clinical applications

    Identified nonparametric model for observations in the control dataset with a 2 charge state

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    (A) The 2-dimensional histogram. (B) The density function curve of the mixed model with 3 Gaussian functions. (C) The error of the density function in each bin. (D) Contour lines of the density function serve as the filter boundaries.<p><b>Copyright information:</b></p><p>Taken from "A nonparametric model for quality control of database search results in shotgun proteomics"</p><p>http://www.biomedcentral.com/1471-2105/9/29</p><p>BMC Bioinformatics 2008;9():29-29.</p><p>Published online 21 Jan 2008</p><p>PMCID:PMC2267700.</p><p></p

    The mesh grids of the DF of M3 and the score distribution of the matches uniquely validated by M1~M3

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    The blue points in B~E represent the matches uniquely validated by M3, the red points are those of M2 and the green points are those of M1.<p><b>Copyright information:</b></p><p>Taken from "A nonparametric model for quality control of database search results in shotgun proteomics"</p><p>http://www.biomedcentral.com/1471-2105/9/29</p><p>BMC Bioinformatics 2008;9():29-29.</p><p>Published online 21 Jan 2008</p><p>PMCID:PMC2267700.</p><p></p

    The partitions of k-means clustering before (A) and after (B) normalization (z-score) of the features

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    Blue and red points represent different clusters. The observations derive from the control dataset. Records with larger and Δare more likely to be positive results. The partition given by k-means clustering using the observed values is based on ; Δhas no effect. After normalization, the partition is more consistent with the empirical knowledge.<p><b>Copyright information:</b></p><p>Taken from "A nonparametric model for quality control of database search results in shotgun proteomics"</p><p>http://www.biomedcentral.com/1471-2105/9/29</p><p>BMC Bioinformatics 2008;9():29-29.</p><p>Published online 21 Jan 2008</p><p>PMCID:PMC2267700.</p><p></p

    Inferred filter boundaries for different charge state observations in the control dataset

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    The pink vertical lines in the +1, +2, and +3 panels are the smallest accepted . The red curves are the filter boundaries for FPR = 0.01, and the green curves are the filter boundaries for FPR = 0.05. The blue points on the -Δplane represent the randomized database matches, and the red points represent the normal database matches. The shape of the boundaries is greatly different for different charge states.<p><b>Copyright information:</b></p><p>Taken from "A nonparametric model for quality control of database search results in shotgun proteomics"</p><p>http://www.biomedcentral.com/1471-2105/9/29</p><p>BMC Bioinformatics 2008;9():29-29.</p><p>Published online 21 Jan 2008</p><p>PMCID:PMC2267700.</p><p></p

    RUPE-phospho: Rapid Ultrasound-Assisted Peptide-Identification-Enhanced Phosphoproteomics Workflow for Microscale Samples

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    Global phosphoproteome profiling can provide insights into cellular signaling and disease pathogenesis. To achieve comprehensive phosphoproteomic analyses with minute quantities of material, we developed a rapid and sensitive phosphoproteomics sample preparation strategy based on ultrasound. We found that ultrasonication-assisted digestion can significantly improve peptide identification by 20% due to the generation of longer peptides that can be detected by mass spectrometry. By integrating this rapid ultrasound-assisted peptide-identification-enhanced proteomic method (RUPE) with streamlined phosphopeptide enrichment steps, we established RUPE-phospho, a fast and efficient strategy to characterize protein phosphorylation in mass-limited samples. This approach dramatically reduces the sample loss and processing time: 24 samples can be processed in 3 h; 5325 phosphosites, 4549 phosphopeptides, and 1888 phosphoproteins were quantified from 5 μg of human embryonic kidney (HEK) 293T cell lysate. In addition, 9219 phosphosites were quantified from 1–2 mg of OCT-embedded mouse brain with 120 min streamlined RUPE-phospho workflow. RUPE-phospho facilitates phosphoproteome profiling for microscale samples and will provide a powerful tool for proteomics-driven precision medicine research

    TRAF6 interacts with STAT3 and mediates the ubiquitination of STAT3.

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    <p>(A) TRAF6 interacts with STAT3 in mammalian cells. Myc-TRAF6 and Flag-STAT3 were co-transfected into HEK293 cells. After 24 h, the cell lysates were immunoprecipitated with anti-Flag antibody and subjected to Western blot with the anti-Flag or anti-Myc antibodies. (B) The cell lysates of HEK293 cells were immunoprecipitated with anti-TRAF6 antibody and subjected to Western blot with the anti-TRAF6 or anti-STAT3 antibodies. (C) Myc-TRAF6 was transfected into HEK293 cells in a dose-dependent manner. After 24 h, the cell lysates were probed with anti-Myc, anti-STAT3 and anti-GAPDH antibodies. (D, E and F) TRAF6 mediates the ubiquitination of STAT3. HA-Ub(WT) (D), HA-Ub(K63R) (E) or HA-Ub(K48R) (F) and Flag-STAT3 were co-expressed in HEK293 cells with Myc-TRAF6 or empty vectors. The cell lysates and immunoprecipitates were resolved by SDS-PAGE and immunoblotted with anti-HA or anti-Flag antibodies. The data are representative of at least three independent experiments.</p

    Searching Missing Proteins Based on the Optimization of Membrane Protein Enrichment and Digestion Process

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    A membrane protein enrichment method composed of ultracentrifugation and detergent-based extraction was first developed based on MCF7 cell line. Then, in-solution digestion with detergents and eFASP (enhanced filter-aided sample preparation) with detergents were compared with the time-consuming in-gel digestion method. Among the in-solution digestion strategies, the eFASP combined with RapiGest identified 1125 membrane proteins. Similarly, the eFASP combined with sodium deoxycholate identified 1069 membrane proteins; however, the in-gel digestion characterized 1091 membrane proteins. Totally, with the five digestion methods, 1390 membrane proteins were identified with ≥1 unique peptides, among which 1345 membrane proteins contain unique peptides ≥2. This is the biggest membrane protein data set for MCF7 cell line and even breast cancer tissue samples. Interestingly, we identified 13 unique peptides belonging to 8 missing proteins (MPs). Finally, eight unique peptides were validated by synthesized peptides. Two proteins were confirmed as MPs, and another two proteins were candidate detections

    The RING finger domain and the TRAF-type zinc finger domain play key roles in the regulation of the transcriptional activity of STAT3.

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    <p>(A) A schematic illustration of TRAF6 domains. The asterisk indicates the expression of TRAF6 mutants that was detected by Western blot with anti-Flag antibody. (B and C) Reporter gene assays of STAT3. HEK293 cells were transiently transfected with various TRAF6 truncated mutants, m67 luciferase plasmids (B) or 4×IRF luciferase plasmids (C), STAT3 and pRL-TK plasmids. After 24 h, the cell lysates were collected for luciferase activity measurements. Data are presented as the means ± S.D. (n = 3).</p
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