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Arch Pathol Lab Med. 2006 Apr;130(4):465-73.

Molecular classification of human cancers using a 92-gene real-time quantitative polymerase chain reaction assay.

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1
Research and Development, Arcturus Bioscience, Inc, Carlsbad, CA 92008, USA.

Abstract

CONTEXT:

Correct diagnosis of the tissue origin of a metastatic cancer is the first step in disease management, but it is frequently difficult using standard pathologic methods. Microarray-based gene expression profiling has shown great promise as a new tool to address this challenge.

OBJECTIVE:

Adoption of microarray technologies in the clinic remains limited. We aimed to bridge this technological gap by developing a real-time quantitative polymerase chain reaction (RT-PCR) assay.

DESIGN:

We constructed a microarray database of 466 frozen and 112 formalin-fixed, paraffin-embedded (FFPE) samples of both primary and metastatic tumors, measuring expression of 22,000 genes. From the microarray database, we used a genetic algorithm to search for gene combinations optimal for multitumor classification. A 92-gene RT-PCR assay was then designed and used to generate a database for 481 frozen and 119 FFPE tumor samples.

RESULTS:

The microarray-based K-nearest neighbor classifier demonstrated 84% accuracy in classifying 39 tumor types via cross-validation and 82% accuracy in predicting 112 independent FFPE samples. We successfully translated the microarray database to the RT-PCR platform, which allowed an overall success rate of 87% in classifying 32 different tumor classes in the validation set of 119 FFPE tumor samples.

CONCLUSIONS:

The RT-PCR-based expression assay involving 92 genes represents a powerful tool for accurately and objectively identifying the site of origin for metastatic tumors, especially in the cases of cancer of unknown primary. The assay uses RT-PCR and routine FFPE samples, making it suitable for rapid clinical adoption.

[Indexed for MEDLINE]

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