Integrative analysis for the discovery of lung cancer serological markers and validation by MRM-MS

Jihye Shin, Sang Yun Song, Hee Sung Ahn, Byung Chull An, Yoo Duk Choi, Eun Gyeong Yang, Kook Joo Na, Seung Taek Lee, Jae Il Park, Seon Young Kim, Cheolju Lee, Seung won Lee

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

Non-small-cell lung cancer (NSCLC) constitutes approximately 80% of all diagnosed lung cancers, and diagnostic markers detectable in the plasma/serum of NSCLC patients are greatly needed. In this study, we established a pipeline for the discovery of markers using 9 transcriptome datasets from publicly available databases and profiling of six lung cancer cell secretomes. Thirty-one out of 312 proteins that overlapped between two-fold differentially expressed genes and identified cell secretome proteins were detected in the pooled plasma of lung cancer patients. To quantify the candidates in the serum of NSCLC patients, multiple-reaction-monitoring mass spectrometry (MRM-MS) was performed for five candidate biomarkers. Finally, two potential biomarkers (BCHE and GPx3; AUC = 0.713 and 0.673, respectively) and one two-marker panel generated by logistic regression (BCHE/GPx3; AUC = 0.773) were identified. A validation test was performed by ELISA to evaluate the reproducibility of GPx3 and BCHE expression in an independent set of samples (BCHE and GPx3; AUC = 0.630 and 0.759, respectively, BCHE/GPx3 panel; AUC = 0.788). Collectively, these results demonstrate the feasibility of using our pipeline for marker discovery and our MRM-MS platform for verifying potential biomarkers of human diseases.

Original languageEnglish
Article numbere0183896
JournalPloS one
Volume12
Issue number8
DOIs
Publication statusPublished - 2017 Aug

All Science Journal Classification (ASJC) codes

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • General

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