Integrative Multianalytical Model Based on Novel Plasma Protein Biomarkers for Distinguishing Lung Adenocarcinoma and Benign Pulmonary Nodules

Given the pressing clinical problem of making a decision in diagnosis for subjects with pulmonary nodules, we aimed to discover novel plasma protein biomarkers for lung adenocarcinoma (LUAD) and benign pulmonary nodules (BPNs) and then develop an integrative multianalytical model to guide the clinic...

Full description

Saved in:
Bibliographic Details
Published in:Journal of proteome research 2024-01, Vol.23 (1), p.277-288
Main Authors: Zhang, Xue, Ji, Longtao, Liu, Man, Li, Jiaqi, Sun, Hao, Liang, Feifei, Zhao, Yutong, Wang, Zhi, Yang, Ting, Wang, Yulin, Si, Qiufang, Du, Renle, Dai, Liping, Ouyang, Songyun
Format: Article
Language:English
Subjects:
Adenocarcinoma of Lung - diagnosis
Aryldialkylphosphatase
Biomarkers
Biomarkers, Tumor
Blood Proteins
Humans
Lung Neoplasms - pathology
Multiple Pulmonary Nodules - diagnosis
Multiple Pulmonary Nodules - pathology
Proteomics
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Given the pressing clinical problem of making a decision in diagnosis for subjects with pulmonary nodules, we aimed to discover novel plasma protein biomarkers for lung adenocarcinoma (LUAD) and benign pulmonary nodules (BPNs) and then develop an integrative multianalytical model to guide the clinical management of LUAD and BPN patients. Through label-free quantitative plasma proteomic analysis (data are available via ProteomeXchange with identifier PXD046731), 12 differentially expressed proteins (DEPs) in LUAD and BPN were screened. The diagnostic abilities of DEPs were validated in two independent validation cohorts. The results showed that the levels of three candidate proteins (PRDX2, PON1, and APOC3) were lower in the plasma of LUAD than in BPN. The three candidate proteins were combined with three promising computed tomography indicators (spiculation, vascular notch sign, and lobulation) and three traditional markers (CEA, CA125, and CYFRA21-1) to construct an integrative multianalytical model, which was effective in distinguishing LUAD from BPN, with an AUC of 0.904, a sensitivity of 81.44%, and a specificity of 90.14%. Moreover, the model possessed impressive diagnostic performance between early LUADs and BPNs, with the AUC, sensitivity, specificity, and accuracy of 0.868, 65.63%, 90.14%, and 82.52%, respectively. This model may be a useful auxiliary diagnostic tool for LUAD and BPN by achieving a better balance of sensitivity and specificity.
ISSN:1535-3893
1535-3907
DOI:10.1021/acs.jproteome.3c00551