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Unlocking biomarker discovery: Large scale application of aptamer proteomic technology for early detection of lung cancer

Ostroff, RM and Bigbee, WL and Franklin, W and Gold, L and Mehan, M and Miller, YE and Pass, HI and Rom, WN and Siegfried, JM and Stewart, A and Walker, JJ and Weissfeld, JL and Williams, S and Zichi, D and Brody, EN (2010) Unlocking biomarker discovery: Large scale application of aptamer proteomic technology for early detection of lung cancer. PLoS ONE, 5 (12).

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Background: Lung cancer is the leading cause of cancer deaths worldwide. New diagnostics are needed to detect early stage lung cancer because it may be cured with surgery. However, most cases are diagnosed too late for curative surgery. Here we present a comprehensive clinical biomarker study of lung cancer and the first large-scale clinical application of a new aptamer-based proteomic technology to discover blood protein biomarkers in disease. Methodology/Principal Findings: We conducted a multi-center case-control study in archived serum samples from 1,326 subjects from four independent studies of non-small cell lung cancer (NSCLC) in long-term tobacco-exposed populations. Sera were collected and processed under uniform protocols. Case sera were collected from 291 patients within 8 weeks of the first biopsy-proven lung cancer and prior to tumor removal by surgery. Control sera were collected from 1,035 asymptomatic study participants with ≥10 pack-years of cigarette smoking. We measured 813 proteins in each sample with a new aptamer-based proteomic technology, identified 44 candidate biomarkers, and developed a 12-protein panel (cadherin-1, CD30 ligand, endostatin, HSP90a, LRIG3, MIP-4, pleiotrophin, PRKCI, RGM-C, SCF-sR, sL-selectin, and YES) that discriminates NSCLC from controls with 91% sensitivity and 84% specificity in cross-validated training and 89% sensitivity and 83% specificity in a separate verification set, with similar performance for early and late stage NSCLC. Conclusions/Significance: This study is a significant advance in clinical proteomics in an area of high unmet clinical need. Our analysis exceeds the breadth and dynamic range of proteome interrogated of previously published clinical studies of broad serum proteome profiling platforms including mass spectrometry, antibody arrays, and autoantibody arrays. The sensitivity and specificity of our 12-biomarker panel improves upon published protein and gene expression panels. Separate verification of classifier performance provides evidence against over-fitting and is encouraging for the next development phase, independent validation. This careful study provides a solid foundation to develop tests sorely needed to identify early stage lung cancer. © 2010 Ostroff et al.


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Item Type: Article
Status: Published
CreatorsEmailPitt UsernameORCID
Ostroff, RM
Bigbee, WL
Franklin, W
Gold, L
Mehan, M
Miller, YE
Pass, HI
Rom, WN
Siegfried, JMjsiegfr@pitt.eduJSIEGFR
Stewart, A
Walker, JJ
Weissfeld, JL
Williams, S
Zichi, D
Brody, EN
ContributionContributors NameEmailPitt UsernameORCID
Date: 20 December 2010
Date Type: Publication
Journal or Publication Title: PLoS ONE
Volume: 5
Number: 12
DOI or Unique Handle: 10.1371/journal.pone.0015003
Schools and Programs: School of Public Health > Epidemiology
Refereed: Yes
MeSH Headings: Algorithms; Autoantibodies--chemistry; Biological Markers--metabolism; Carcinoma, Non-Small-Cell Lung--metabolism; Case-Control Studies; Cohort Studies; Early Detection of Cancer--methods; Humans; Lung Neoplasms--metabolism; Mass Spectrometry--methods; Models, Statistical; Proteomics--methods; Sensitivity and Specificity; Smoking--adverse effects; Tumor Markers, Biological--metabolism
Other ID: NLM PMC2999620
PubMed Central ID: PMC2999620
PubMed ID: 21170350
Date Deposited: 22 Aug 2012 22:00
Last Modified: 02 Feb 2019 14:55


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