L Wang1, H Y Liu2, H H Shi1, J H Lang1, W Sun3. 1. Department of Obstetrics and Gynecology, Peking Union Medical College Hospital (PUMCH), Chinese Academy of Medical Science (CAMS), Beijing, China. 2. Department of Obstetrics and Gynecology, Peking Union Medical College Hospital (PUMCH), Chinese Academy of Medical Science (CAMS), Beijing, China. Electronic address: haiyuanliu@163.com. 3. Proteomic Center, Peking Union Medical College (PUMC) & CAMS, Beijing, China.
Abstract
OBJECTIVE: To detect endometriosis by urine peptide biomarkers using magnetic beads-based matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) and to identify interesting peptides using liquid chromatography tandem mass spectrometry. STUDY DESIGN: Prospective case-control study in a university-based gynecological department and central laboratory. A total of 122 patients suffering from dysmenorrhea, pelvic pain and infertility were enrolled in the study. Urine samples were collected before laparoscopy. Urine samples were analyzed by the MALDI-TOF technique to generate peptide profiling and ClinProTools software was used to set up a diagnostic model for endometriosis. Liquid chromatography tandem mass spectrometry (LC-MS/MS) was used to identify interesting peptides. RESULTS: At laparoscopy 60 patients were diagnosed with endometriosis and 62 patients were disease-free. There were 36 different peptides expressed in endometriosis patients detected by MALDI-TOF compared with controls. We established a genetic algorithm as a diagnostic model with the combination of five peptides (m/z=1433.9, 1599.4, 2085.6, 6798.0 and 3217.2). The model showed a sensitivity of 90.9% and specificity of 92.9%. Urine from another 26 symptomatic patients before laparoscopy were randomly selected and analyzed accordingly. A genetic algorithm showed a sensitivity of 90.9% and specificity of 92.9% in predicting endometriosis before laparoscopy. We also identified two peptides not belonging to the diagnostic model as collagen precursors. CONCLUSIONS: Patients with endometriosis have a unique cluster of peptides in urine. Peptide proteomic profiling provides a novel method for non-invasive diagnosis of endometriosis.
OBJECTIVE: To detect endometriosis by urine peptide biomarkers using magnetic beads-based matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) and to identify interesting peptides using liquid chromatography tandem mass spectrometry. STUDY DESIGN: Prospective case-control study in a university-based gynecological department and central laboratory. A total of 122 patients suffering from dysmenorrhea, pelvic pain and infertility were enrolled in the study. Urine samples were collected before laparoscopy. Urine samples were analyzed by the MALDI-TOF technique to generate peptide profiling and ClinProTools software was used to set up a diagnostic model for endometriosis. Liquid chromatography tandem mass spectrometry (LC-MS/MS) was used to identify interesting peptides. RESULTS: At laparoscopy 60 patients were diagnosed with endometriosis and 62 patients were disease-free. There were 36 different peptides expressed in endometriosispatients detected by MALDI-TOF compared with controls. We established a genetic algorithm as a diagnostic model with the combination of five peptides (m/z=1433.9, 1599.4, 2085.6, 6798.0 and 3217.2). The model showed a sensitivity of 90.9% and specificity of 92.9%. Urine from another 26 symptomatic patients before laparoscopy were randomly selected and analyzed accordingly. A genetic algorithm showed a sensitivity of 90.9% and specificity of 92.9% in predicting endometriosis before laparoscopy. We also identified two peptides not belonging to the diagnostic model as collagen precursors. CONCLUSIONS:Patients with endometriosis have a unique cluster of peptides in urine. Peptide proteomic profiling provides a novel method for non-invasive diagnosis of endometriosis.
Authors: Emily Liu; Vicki Nisenblat; Cindy Farquhar; Ian Fraser; Patrick M M Bossuyt; Neil Johnson; M Louise Hull Journal: Cochrane Database Syst Rev Date: 2015-12-23
Authors: Panagiotis Giamougiannis; Camilo L M Morais; Brice Rodriguez; Nicholas J Wood; Pierre L Martin-Hirsch; Francis L Martin Journal: Anal Bioanal Chem Date: 2021-07-01 Impact factor: 4.142