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

doi:10.1371/journal.pone.0183896

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 journal › Article › peer-review

12 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 language	English
Article number	e0183896
Journal	PloS one
Volume	12
Issue number	8
DOIs	https://doi.org/10.1371/journal.pone.0183896
Publication status	Published - 2017 Aug

Bibliographical note

Funding Information:
The study was supported by grants from the National Research Foundation of Korea (NRF-2017M3A9F9030559, NRF-2017M3A9F9030565) and Korea Health Industry Development Institute (HI14C3484) to CL. This study was also supported by a grant (CRI 15023-21) from the Chonnam National University Hospital Biomedical Research Institute to SWL. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Publisher Copyright:
© 2017 Shin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

All Science Journal Classification (ASJC) codes

Biochemistry, Genetics and Molecular Biology(all)
Agricultural and Biological Sciences(all)
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@article{693c4bccaf9646169c22b3171ac2b131,

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

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.",

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

note = "Funding Information: The study was supported by grants from the National Research Foundation of Korea (NRF-2017M3A9F9030559, NRF-2017M3A9F9030565) and Korea Health Industry Development Institute (HI14C3484) to CL. This study was also supported by a grant (CRI 15023-21) from the Chonnam National University Hospital Biomedical Research Institute to SWL. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Publisher Copyright: {\textcopyright} 2017 Shin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.",

year = "2017",

month = aug,

doi = "10.1371/journal.pone.0183896",

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volume = "12",

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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 journal › Article › peer-review

TY - JOUR

T1 - Integrative analysis for the discovery of lung cancer serological markers and validation by MRM-MS

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

N1 - Funding Information: The study was supported by grants from the National Research Foundation of Korea (NRF-2017M3A9F9030559, NRF-2017M3A9F9030565) and Korea Health Industry Development Institute (HI14C3484) to CL. This study was also supported by a grant (CRI 15023-21) from the Chonnam National University Hospital Biomedical Research Institute to SWL. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Publisher Copyright: © 2017 Shin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

UN SDGs

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