Literature DB >> 23287002

Blinded comparator study of immunohistochemical analysis versus a 92-gene cancer classifier in the diagnosis of the primary site in metastatic tumors.

Lawrence M Weiss1, Peiguo Chu, Brock E Schroeder, Veena Singh, Yi Zhang, Mark G Erlander, Catherine A Schnabel.   

Abstract

Accurate tumor classification is fundamental to inform predictive biomarker testing and optimize therapy. Gene expression-based tests are proposed as diagnostic aids in cases with uncertain diagnoses. This study directly compared the diagnostic accuracy of IHC analysis versus molecular classification using a 92-gene RT-PCR assay for determination of the primary tumor site. This prospectively defined blinded study of diagnostically challenging cases included 131 high-grade, primarily metastatic tumors. Cases were reviewed and reference diagnoses established through clinical correlation. Blinded FFPE sections were evaluated by either IHC/morphology analysis or the 92-gene assay. The final analysis included 122 cases. The 92-gene assay demonstrated overall accuracy of 79% (95% CI, 71% to 85%) for tumor classification versus 69% (95% CI, 60% to 76%) for IHC/morphology analysis (P = 0.019). Mean IHC use was 7.9 stains per case (median, 8; range, 2 to 15). IHC/morphology analysis accuracy was 79%, 80%, and 46% when 1 to 6 (n = 42), 7 to 9 (n = 41), and >9 (n = 39) IHC stains were used, respectively, versus 81%, 85%, and 69%, respectively, with the 92-gene assay. Results from this blinded series of high-grade metastatic cases demonstrate superior accuracy with the 92-gene assay versus standard-of-care IHC analysis and strongly support the diagnostic utility of molecular classification in difficult-to-diagnose metastatic cancer.
Copyright © 2013 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 23287002     DOI: 10.1016/j.jmoldx.2012.10.001

Source DB:  PubMed          Journal:  J Mol Diagn        ISSN: 1525-1578            Impact factor:   5.568


  26 in total

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