Multisite validation study to determine performance characteristics of a 92-gene molecular cancer classifier.
OBJECTIVE
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.


METHODS
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.


RESULTS
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.


CONCLUSIONS
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.
Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
Sarah E
SE
Kerr
Catherine A
CA
Schnabel
Peggy S
PS
Sullivan
Yi
Y
Zhang
Veena
V
Singh
Brittany
B
Carey
Mark G
MG
Erlander
W Edward
WE
Highsmith
Sarah M
SM
Dry
Elena F
EF
Brachtel
D000328:Adult; D000368:Aged; D014408:Biomarkers, Tumor / Q000235:genetics / Q000378:metabolism; D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D008297:Male; D008875:Middle Aged; D009367:Neoplasm Staging; D009369:Neoplasms / Q000145:classification* / Q000378:metabolism / Q000473:pathology; D020411:Oligonucleotide Array Sequence Analysis; D016612:Paraffin Embedding; D011379:Prognosis; D011506:Proteins / Q000235:genetics
D014408:Biomarkers, Tumor; D011506:Proteins