Literature DB >> 22425918

A multiplexed serum biomarker immunoassay panel discriminates clinical lung cancer patients from high-risk individuals found to be cancer-free by CT screening.

William L Bigbee1, Vanathi Gopalakrishnan, Joel L Weissfeld, David O Wilson, Sanja Dacic, Anna E Lokshin, Jill M Siegfried.   

Abstract

INTRODUCTION: Clinical decision making in the setting of computed tomography (CT) screening could benefit from accessible biomarkers that help predict the level of lung cancer risk in high-risk individuals with indeterminate pulmonary nodules.
METHODS: To identify candidate serum biomarkers, we measured 70 cancer-related proteins by Luminex xMAP (Luminex Corporation) multiplexed immunoassays in a training set of sera from 56 patients with biopsy-proven primary non-small-cell lung cancer and 56 age-, sex-, and smoking-matched CT-screened controls.
RESULTS: We identified a panel of 10 serum biomarkers-prolactin, transthyretin, thrombospondin-1, E-selectin, C-C motif chemokine 5, macrophage migration inhibitory factor, plasminogen activator inhibitor, receptor tyrosine-protein kinase, erbb-2, cytokeratin fragment 21.1, and serum amyloid A-that distinguished lung cancer patients from controls with an estimated balanced accuracy (average of sensitivity and specificity) of 76.0 ± 3.8% from 20-fold internal cross-validation. We then iteratively evaluated this model in an independent test and verification case/control studies confirming the initial classification performance of the panel. The classification performance of the 10-biomarker panel was also analytically validated using enzyme-linked immunosorbent assays in a second independent case/control population, further validating the robustness of the panel.
CONCLUSIONS: The performance of this 10-biomarker panel-based model was 77.1% sensitivity/76.2% specificity in cross-validation in the expanded training set, 73.3% sensitivity/93.3% specificity (balanced accuracy 83.3%) in the blinded verification set with the best discriminative performance in stage I/II cases: 85% sensitivity (balanced accuracy 89.2%). Importantly, the rate of misclassification of CT-screened controls was not different in most control subgroups with or without airflow obstruction or emphysema or pulmonary nodules. These biomarkers have potential to aid in the early detection of lung cancer and more accurate interpretation of indeterminate pulmonary nodules detected by CT screening.

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Year:  2012        PMID: 22425918      PMCID: PMC3308353          DOI: 10.1097/JTO.0b013e31824ab6b0

Source DB:  PubMed          Journal:  J Thorac Oncol        ISSN: 1556-0864            Impact factor:   15.609


  46 in total

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2.  Diagnostic accuracy of MALDI mass spectrometric analysis of unfractionated serum in lung cancer.

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4.  Lung cancer signatures in plasma based on proteome profiling of mouse tumor models.

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Journal:  Cancer Sci       Date:  2007-08-07       Impact factor: 6.716

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  36 in total

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8.  Assessment of Lung Cancer Risk on the Basis of a Biomarker Panel of Circulating Proteins.

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9.  A blood-based proteomic classifier for the molecular characterization of pulmonary nodules.

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