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An integrated proteomic classifier to distinguish benign from malignant pulmonary nodules

  • Bin Jia
  • , Tingting Wang
  • , Liangxuan Pan
  • , Xiaoyao Du
  • , Jing Yang
  • , Fei Gao
  • , Lujian Liao
  • , Bianqin Guo*
  • , Junqiang Dong*
  • *此作品的通讯作者
  • The First Affiliated Hospital of Zhengzhou University
  • Durbrain Medical Laboratory
  • Chongqing University Cancer Hospital

科研成果: 期刊稿件文章同行评审

摘要

Background: Pulmonary nodule with diameters ranging 8–30 mm has a high occurrence rate, and distinguishing benign from malignant nodules can greatly improve the patient outcome of lung cancer. However, sensitive and specific liquid-biopsy methods have yet to achieve satisfactory clinical goals. Methods: We enrolled three cohorts and a total of 185 patients diagnosed with benign (BE) and malignant (MA) pulmonary nodules. Utilizing data-independent acquisition (DIA) mass spectrometry, we quantified plasma proteome from these patients. We then performed logistic regression analysis to classify benign from malignant nodules, using cohort 1 as discovery data set and cohort 2 and 3 as independent validation data sets. We also developed a targeted multi-reaction monitoring (MRM) method to measure the concentration of the selected six peptide markers in plasma samples. Results: We quantified a total of 451 plasma proteins, with 15 up-regulated and 5 down-regulated proteins from patients diagnosed as having malignant nodules. Logistic regression identified a six-protein panel comprised of APOA4, CD14, PFN1, APOB, PLA2G7, and IGFBP2 that classifies benign and malignant nodules with improved accuracy. In cohort 1, the area under curve (AUC) of the training and testing reached 0.87 and 0.91, respectively. We achieved a sensitivity of 100%, specificity of 40%, positive predictive value (PPV) of 62.5%, and negative predictive value (NPV) of 100%. In two independent cohorts, the 6-biomarker panel showed a sensitivity, specificity, PPV, and NPV of 96.2%, 35%, 65.8%, and 87.5% respectively in cohort 2, and 91.4%, 54.2%, 74.4%, and 81.3% respectively in cohort 3. We performed a targeted LC-MS/MS method to quantify plasma concentration of the six peptides and applied logistic regression to classify benign and malignant nodules with AUC of the training and testing reached 0.758 and 0.751, respectively. Conclusions: Our study identified a panel of plasma protein biomarkers for distinguishing benign from malignant pulmonary nodules that worth further development into a clinically valuable assay.

源语言英语
文章编号11
期刊Clinical Proteomics
22
1
DOI
出版状态已出版 - 12月 2025
已对外发布

联合国可持续发展目标

此成果有助于实现下列可持续发展目标:

  1. 可持续发展目标 3 - 良好健康与福祉
    可持续发展目标 3 良好健康与福祉

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