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Figure S2 from High-Throughput Peptide Arrays Identify Potential Diagnostic Autoantibody Signatures in Early-Stage Lung Adenocarcinoma

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posted on 2023-03-29, 14:00 authored by Rongrong Luo, Pei Zhong, Xiying Li, Juan Cai, Yimin Tao, Bangzhu Xiong, Hancheng Zheng, Zhishang Zhang, Le Tang, Jiarui Yao, Yingrui Li, Yuankai Shi, Xiaohong Han

Corresponding signal of previous reported autoantibodies for early lung cancer detection were evaluated in our study cohort with both HuProtTM protein microarray (detail data not shown) and peptide array. All peptides were aligned to 10 proteins using blastp method, 246 peptides were mapped under the set of e-value of 1 and identity of 90. Accumulated peptide signal was set as autoantibody signal of corresponding antigen protein. Nine autoantibodies had effective testing value in HuprotTM. a.t test P value of autoantibodies signals for Early-LUAD versus NHC from peptide array and HuProtTM detection respectively. Two autoantibodies from peptide array and 2 autoantibodies from HuProtTM showed higher signal in Early-LUAD group under P <0.05. Five autoantibodies from peptide array and 2 autoantibodies from HuProtTM showed higher signal in Early-LUAD group under P < 0.1.b.Volcano plot of peptides signals corresponding to 10 autoantigens. X-axis represents the log10 of the fold change, y-axis represents -log10 (P adjust) for Early-LUAD versus NHC. Significantly up-regulated and down-regulated peptides in Early-LUAD group are shown in light red and blue. Two hundred and forty-six peptides mapped to the 10 autoantibodies were shown in green, and 8 significantly upregulated peptides in Early-LUAD shown in green cross. No intersection between the green mapped signals and the peptides used for classifier model (dark red).

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ARTICLE ABSTRACT

Early diagnosis is critical to lung adenocarcinoma patients’ survival but faces inadequacies in convenient early detection. We applied a comprehensive microarray of 130,000 peptides to detect “autoantibody signature” that is autoantibodies binding to mimotopes for early detection of stage 0–I LUAD. Plasma samples were collected from 147 early-stage lung adenocarcinoma (Early-LUAD), 108 benign lung disease (BLD), and 122 normal healthy controls (NHC). Clinical characteristics, low-dose CT (LDCT), and laboratory tests were incorporated into correlation analysis. We identified 143 and 133 autoantibody signatures, distinguishing Early-LUAD from NHC/BLD in the discovery cohort. Autoantibody signatures significantly correlated with age, stage, tumor size, basophil count, and IgM level (P < 0.05). The random forest models based on differential autoantibody signatures displayed AUC of 0.92 and 0.87 to discern Early-LUAD from NHC/BLD in the validation cohort, respectively. Compared with LDCT, combining autoantibody signature and LDCT improved the positive predictive value from 50% to 78.33% (P = 0.049). In addition, autoantibody signatures displayed higher sensitivity of 72.4% to 81.0% compared with the combinational tumor markers (cyfra21.1, NSE, SCC, ProGRP) with a sensitivity of 22.4% (P = 0.000). Proteins matched by differential peptides were enriched in cancer-related PI3K/Akt, MAPK, and Wnt pathways. Overlaps between matched epitopes and autoantibody signatures illustrated the underlying engagement of autoantibodies in immune recognition. Collectively, autoantibody signatures identified by a high-throughput peptide microarray have the potential to detect Early-LUAD, which could assist LDCT to better diagnose Early-LUAD. Novel sensitive autoantibody signatures can adjuvant LDCT to better diagnose LUAD at very early stage.

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    Cancer Epidemiology, Biomarkers & Prevention

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