High-throughput detection of fusion genes in cancer using the Sequenom MassARRAY platform.
Lab Invest
; 91(10): 1491-501, 2011 Oct.
Article
em En
| MEDLINE
| ID: mdl-21808235
Fusion genes have pivotal roles in the development and progression of human cancer and offer potential for rational drug design. Massively parallel sequencing has identified a panoply of in-frame expressed fusion genes, but early reports suggest that the majority of these are present at very low prevalence or are private events. Conventional methods for the identification of recurrent expressed fusion genes in large cohorts of cancers (eg fluorescence in situ hybridization (FISH) and reverse transcriptase PCR (RT-PCR)) are time consuming and prone to artifacts. Here, we describe a novel high-throughput strategy for the detection of recurrent fusion genes in cancer based on the Sequenom MassARRAY platform. Fusion genes were initially identified by massively parallel sequencing of breast cancer cell lines. For each fusion gene, two Sequenom probes were designed. Primary human breast cancers and cancer cell lines were interrogated for 10 fusion genes. Sensitivity, specificity, and predictive values of the MassARRAY method were then determined using FISH and qRT-PCR as the 'gold standard.' By combining two probes per fusion gene, the negative and positive predictive values were 100 and 71.4%, respectively. All fusion genes identified by massively parallel sequencing were accurately detected. No recurrent fusion genes were found. The MassARRAY-based approach described here may, therefore, be employed as a high-throughput screening tool for known fusion genes in human cancer. In keeping with other highly sensitive assays, further refinement of this technique is necessary to reduce the number of false-positive results.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Neoplasias da Mama
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Proteínas de Fusão Oncogênica
/
Análise em Microsséries
/
Sequenciamento de Nucleotídeos em Larga Escala
Tipo de estudo:
Diagnostic_studies
/
Evaluation_studies
/
Prognostic_studies
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Risk_factors_studies
Limite:
Female
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Humans
Idioma:
En
Revista:
Lab Invest
Ano de publicação:
2011
Tipo de documento:
Article