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Cancer. 2012 Mar 15;118(6):1607-18. doi: 10.1002/cncr.26450. Epub 2011 Aug 25.

Molecular classification of nonsmall cell lung cancer using a 4-protein quantitative assay.

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  • 1Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA. valsamo.anagnostou@yale.edu

Abstract

BACKGROUND:

The importance of definitive histological subclassification has increased as drug trials have shown benefit associated with histology in nonsmall-cell lung cancer (NSCLC). The acuity of this problem is further exacerbated by the use of minimally invasive cytology samples. Here we describe the development and validation of a 4-protein classifier that differentiates primary lung adenocarcinomas (AC) from squamous cell carcinomas (SCC).

METHODS:

Quantitative immunofluorescence (AQUA) was employed to measure proteins differentially expressed between AC and SCC followed by logistic regression analysis. An objective 4-protein classifier was generated to define likelihood of AC in a training set of 343 patients followed by validation in 2 independent cohorts (n = 197 and n = 235). The assay was then tested on 11 cytology specimens.

RESULTS:

Statistical modeling selected thyroid transcription factor 1 (TTF1), CK5, CK13, and epidermal growth factor receptor (EGFR) to generate a weighted classifier and to identify the optimal cutpoint for differentiating AC from SCC. Using the pathologist's final diagnosis as the criterion standard, the molecular test showed a sensitivity of 96% and specificity of 93%. Blinded analysis of the validation sets yielded sensitivity and specificity of 96% and 97%, respectively. Our assay classified the cytology specimens with a specificity of 100% and sensitivity of 87.5%.

CONCLUSIONS:

Molecular classification of NSCLC using an objective quantitative test can be highly accurate and could be translated into a diagnostic platform for broad clinical application.

Copyright © 2011 American Cancer Society.

PMID:
22009766
[PubMed - indexed for MEDLINE]
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