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

7 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

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Biomarkers
lung neoplasms
Area Under Curve
Mass spectrometry
Lung Neoplasms
Mass Spectrometry
Non-Small Cell Lung Carcinoma
mass spectrometry
Monitoring
monitoring
Pipelines
Cells
Plasmas
biomarkers
Logistics
Proteins
Genes
Serum
Transcriptome
cells

All Science Journal Classification (ASJC) codes

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

Cite this

Shin, J., Song, S. Y., Ahn, H. S., An, B. C., Choi, Y. D., Yang, E. G., ... Lee, S. W. (2017). Integrative analysis for the discovery of lung cancer serological markers and validation by MRM-MS. PloS one, 12(8), [e0183896]. https://doi.org/10.1371/journal.pone.0183896
Shin, Jihye ; Song, Sang Yun ; Ahn, Hee Sung ; An, Byung Chull ; Choi, Yoo Duk ; Yang, Eun Gyeong ; Na, Kook Joo ; Lee, Seung Taek ; Park, Jae Il ; Kim, Seon Young ; Lee, Cheolju ; Lee, Seung won. / Integrative analysis for the discovery of lung cancer serological markers and validation by MRM-MS. In: PloS one. 2017 ; Vol. 12, No. 8.
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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.",
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Shin, J, Song, SY, Ahn, HS, An, BC, Choi, YD, Yang, EG, Na, KJ, Lee, ST, Park, JI, Kim, SY, Lee, C & Lee, SW 2017, 'Integrative analysis for the discovery of lung cancer serological markers and validation by MRM-MS', PloS one, vol. 12, no. 8, e0183896. https://doi.org/10.1371/journal.pone.0183896

Integrative analysis for the discovery of lung cancer serological markers and validation by MRM-MS. / Shin, Jihye; Song, Sang Yun; Ahn, Hee Sung; An, Byung Chull; Choi, Yoo Duk; Yang, Eun Gyeong; Na, Kook Joo; Lee, Seung Taek; Park, Jae Il; Kim, Seon Young; Lee, Cheolju; Lee, Seung won.

In: PloS one, Vol. 12, No. 8, e0183896, 08.2017.

Research output: Contribution to journalArticle

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AU - Shin, Jihye

AU - Song, Sang Yun

AU - Ahn, Hee Sung

AU - An, Byung Chull

AU - Choi, Yoo Duk

AU - Yang, Eun Gyeong

AU - Na, Kook Joo

AU - Lee, Seung Taek

AU - Park, Jae Il

AU - Kim, Seon Young

AU - Lee, Cheolju

AU - Lee, Seung won

PY - 2017/8

Y1 - 2017/8

N2 - 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.

AB - 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.

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