ArticleDiagnostic pathology2013
A gene expression profile test to resolve head & neck squamous versus lung squamous cancers.
Article in Diagnostic pathology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Cancer of unknown primary: the evolution of tissue of origin identification in the artificial intelligence era.Biomarker research · 2026Review
- Article
- Gene expression profiling for the diagnosis of multiple primary malignant tumors.Cancer cell international · 2021Article
- Evaluating DNA Methylation, Gene Expression, Somatic Mutation, and Their Combinations in Inferring Tumor Tissue-of-Origin.Frontiers in cell and developmental biology · 2021Article
- Oncology Scan: Radiation Biology and Genomic Predictors of Response.International journal of radiation oncology, biology, physics · 2020Article
- Rapid Nanophotonics Assay for Head and Neck Cancer Diagnosis.Scientific reports · 2018Article
- Article
- Combined effects of 17-DMAG and TNF on cells through a mechanism related to the NF-kappaB pathway.Diagnostic pathology · 2013Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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.
methodsThe 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.
resultsThe 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%.
conclusionGEP-HN-LS can aid in resolving the important differential diagnosis between HNSCC and lung SCC tumors. VIRTUAL SLIDES: The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1753227817890930.
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