Multisite validation study to determine performance characteristics of a 92-gene molecular cancer classifier.
prospective_cohort · Level II
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- Record sourced from PubMed, PMID 22648269.
- Also identified by DOI 10.1158/1078-0432.CCR-12-0920.
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Abstract
Accurate tumor classification is essential for cancer management as patient outcomes improve with use of site- and subtype-specific therapies. Current clinicopathologic evaluation is varied in approach, yet standardized diagnoses are critical for determining therapy. While gene expression-based cancer classifiers may potentially meet this need, imperative to determining their application to patient care is validation in rigorously designed studies. Here, we examined the performance of a 92-gene molecular classifier in a large multi-institution cohort. Case selection incorporated specimens from more than 50 subtypes, including a range of tumor grades, metastatic and primary tumors, and limited tissue samples. Formalin-fixed, paraffin-embedded tumors passed pathologist-adjudicated review between three institutions. Tumor classification using a 92-gene quantitative reverse transcriptase polymerase chain reaction (RT-PCR) assay was conducted on blinded tumor sections from 790 cases and compared with adjudicated diagnoses. The 92-gene assay showed overall sensitivities of 87% for tumor type [95% confidence interval (CI), 84-89] and 82% for subtype (95% CI, 79-85). Analyses of metastatic tumors, high-grade tumors, or cases with limited tissue showed no decrease in comparative performance (P = 0.16, 0.58, and 0.16). High specificity (96%-100%) was showed for ruling in a primary tumor in organs commonly harboring metastases. The assay incorrectly excluded the adjudicated diagnosis in 5% of cases. The 92-gene assay showed strong performance for accurate molecular classification of a diverse set of tumor histologies. Results support potential use of the assay as a standardized molecular adjunct to routine clinicopathologic evaluation for tumor classification and primary site diagnosis.
Medical subject headings
- Biomarkers, Tumor
- Gene Expression Profiling
- Neoplasms
- Proteins