báo cáo hóa học:" A large, consistent plasma proteomics data set from prospectively collected breast cancer patient and healthy volunteer samples"

Tuyển tập các báo cáo nghiên cứu về hóa học được đăng trên tạp chí sinh học đề tài : A large, consistent plasma proteomics data set from prospectively collected breast cancer patient and healthy volunteer samples | Riley et al. Journal of Translational Medicine 2011 9 80 http content 9 1 80 JOURNAL OF TRANSLATIONAL MEDICINE RESEARCH Open Access A large consistent plasma proteomics data set from prospectively collected breast cancer patient and healthy volunteer samples 1 2 3 4 1 1 Catherine P Riley Xiang Zhang Harikrishna Nakshatri Bryan Schneider Fred E Regnier Jiri Adamec and Charles Buck1 Abstract Background Variability of plasma sample collection and of proteomics technology platforms has been detrimental to generation of large proteomic profile datasets from human biospecimens. Methods We carried out a clinical trial-like protocol to standardize collection of plasma from 204 healthy and 216 breast cancer patient volunteers. The breast cancer patients provided follow up samples at 3 month intervals. We generated proteomics profiles from these samples with a stable and reproducible platform for differential proteomics that employs a highly consistent nanofabricated ChipCube chromatography system for peptide detection and quantification with fast single dimension mass spectrometry LC-MS . Protein identification is achieved with subsequent LC-MS MS analysis employing the same ChipCube chromatography system. Results With this consistent platform over 800 LC-MS plasma proteomic profiles from prospectively collected samples of 420 individuals were obtained. Using a web-based data analysis pipeline for LC-MS profiling data analyses of all peptide peaks from these plasma LC-MS profiles reveals an average coefficient of variability of less than 15 . Protein identification of peptide peaks of interest has been achieved with subsequent LC-MS MS analyses and by referring to a spectral library created from about 150 discrete LC-MS MS runs. Verification of peptide quantity and identity is demonstrated with several Multiple Reaction Monitoring analyses. These plasma proteomic profiles are publicly available through ProteomeCommons. Conclusion From a large

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