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Published in: Diagnostic Pathology 1/2013

Open Access 01-12-2013 | Research

A gene expression profile test to resolve head & neck squamous versus lung squamous cancers

Authors: Anita Lal, Rebecca Panos, Mira Marjanovic, Michael Walker, Eloisa Fuentes, Gregory J Kubicek, W David Henner, Ljubomir J Buturovic, Meredith Halks-Miller

Published in: Diagnostic Pathology | Issue 1/2013

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Abstract

Background

The differential diagnosis between metastatic head & neck squamous cell carcinomas (HNSCC) and lung squamous cell carcinomas (lung SCC) is often unresolved because the histologic appearance of these two tumor types is similar. We have developed and validated a gene expression profile test (GEP-HN-LS) that distinguishes HNSCC and lung SCC in formalin-fixed, paraffin-embedded (FFPE) specimens using a 2160–gene classification model.

Methods

The test was validated in a blinded study using a pre-specified algorithm and microarray data files for 76 metastatic or poorly-differentiated primary tumors with a known HNSCC or lung SCC diagnosis.

Results

The study met the primary Bayesian statistical endpoint for acceptance. Measures of test performance include overall agreement with the known diagnosis of 82.9% (95% CI, 72.5% to 90.6%), an area under the ROC curve (AUC) of 0.91 and a diagnostics odds ratio (DOR) of 23.6. HNSCC (N = 38) gave an agreement with the known diagnosis of 81.6% and lung SCC (N = 38) gave an agreement of 84.2%. Reproducibility in test results between three laboratories had a concordance of 91.7%.

Conclusion

GEP-HN-LS can aid in resolving the important differential diagnosis between HNSCC and lung SCC tumors.

Virtual Slides

Appendix
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Metadata
Title
A gene expression profile test to resolve head & neck squamous versus lung squamous cancers
Authors
Anita Lal
Rebecca Panos
Mira Marjanovic
Michael Walker
Eloisa Fuentes
Gregory J Kubicek
W David Henner
Ljubomir J Buturovic
Meredith Halks-Miller
Publication date
01-12-2013
Publisher
BioMed Central
Published in
Diagnostic Pathology / Issue 1/2013
Electronic ISSN: 1746-1596
DOI
https://doi.org/10.1186/1746-1596-8-44

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