Label‐Free Quantitative Proteomics Identifies Novel Biomarkers for Distinguishing Tuberculosis Pleural Effusion from Malignant Pleural Effusion. Issue 1 (24th November 2019)

• Record Type: Journal Article
• Authors: Pan, Liping; Zhang, Xia; Jia, Hongyan; Huang, Mailing; Liu, Fei; Wang, Jinghui; Du, Boping; Wei, Rongrong; Sun, Qi; Xing, Aiying; Li, Qi; Zhang, Zongde
• Is Part Of: Proteomics. Volume 14:Issue 1(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-11-24
• Subjects: diagnostic model -- label‐free quantitative proteomics -- malignant pleural effusion -- protein biomarkers -- tuberculosis pleural effusion; Proteomics -- Periodicals; 572.605
• DOI: 10.1002/prca.201900001
• Languages: English
• ISSNs: 1862-8346

Abstract

Abstract : Purpose: To identify potential protein biomarkers for distinguishing tuberculosis plural effusion (TBPE) from malignant plural effusion (MPE). Experimental design: Five independent samples from each group (TBPE and MPE) are enrolled for label‐free quantitative proteomics analyses. The differentially expressed proteins are validated by western blot and ELISA. Logistic regression analysis is used to obtain the optimal diagnostic model. Results: In total, 14 proteins with significant difference are identified between TBPE and MPE. Seven differentially expressed proteins are validated using western blot, and the expression patterns of these seven proteins are similar with those in proteomics analysis. Statistically significant differences in four proteins (AGP1, ORM2, C9, and SERPING1) are noted between TBPE and MPE in the training set ( n = 230). Logistic regression analysis shows the combination of AGP1–ORM2–C9 presents a sensitivity of 73.0% (92/126) and specificity of 89.4% (93/104) in discriminating TBPE from MPE. Additional validation is performed to evaluate the diagnostic model in an independent blind testing set ( n = 80), and yielded a sensitivity of 74.4% (32/43) and specificity of 91.9% (34/37) in discriminating TBPE from MPE. Conclusion: The study uncovers the proteomic profiles of TBPE and MPE, and provides new potential diagnostic biomarkers for distinguishing TBPE from MPE.