RESUMEN
Family structure, lack of reliable information, cost, and delay are usual concerns when deciding to perform BRCA analyses. Testing breast cancer tissues with four antibodies (MS110, lys27H3, vimentin, and KI67) in addition to grade evaluation enabled us to rapidly select patients for genetic testing identification. We constituted an initial breast cancer tissue microarray, considered as a learning set, comprising 27 BRCA1 and 81 sporadic tumors. A second independent validation set of 28 BRCA1 tumors was matched to 28 sporadic tumors using the same original conditions. We investigated morphological parameters and 21 markers by immunohistochemistry. A logistic regression model was used to select the minimal number of markers providing the best model to predict BRCA1 status. The model was applied to the validation set to estimate specificity and sensibility. In the initial set, univariate analyses identified 11 markers significantly associated with BRCA1 status. Then, the best multivariate model comprised only grade 3, MS110, Lys27H3, vimentin, and KI67. When applied to the validation set, BRCA1 tumors were correctly classified with a sensitivity of 83% and a specificity of 81%. The performance of this model was superior when compared to other profiles. This study offers a new rapid and cost-effective method for the prescreening of patients at high risk of being BRCA1 mutation carriers, to guide genetic testing, and finally to provide appropriate preventive measures, advice, and treatments including targeted therapy to patients and their families.
Asunto(s)
Proteína BRCA1/genética , Neoplasias de la Mama/diagnóstico , Mutación de Línea Germinal , Histonas/análisis , Antígeno Ki-67/análisis , Vimentina/análisis , Proteína BRCA1/análisis , Neoplasias de la Mama/química , Neoplasias de la Mama/genética , Neoplasias de la Mama/patología , Análisis Mutacional de ADN , Femenino , Predisposición Genética a la Enfermedad , Pruebas Genéticas , Humanos , Inmunohistoquímica , Modelos Logísticos , Lisina , Análisis Multivariante , Clasificación del Tumor , Selección de Paciente , Fenotipo , Valor Predictivo de las Pruebas , Pronóstico , Reproducibilidad de los Resultados , Análisis de Matrices TisularesRESUMEN
The progress in the knowledge of molecular genetics and the availability of high-throughput technologies offer the opportunity to identify new diagnostic and prognostic markers and new therapeutic targets in human cancer. The recently developed "tissue microarraysî (TMA) technology allows parallel molecular profiling of clinical samples. Using this technique and immunohistochemistry (IHC), fluorescence in situ hybridisation (FISH), or RNA in situ hybridisation (ISH), the pathologist is now able to perform unprecedented large-scale analyses. The advantages are significant: large number of cases assessed simultaneously for numerous markers, processing in identical conditions, reduced amount of archival tissues, excellent correlation with standard methods, reduction in cost and time. This article provides a short review of this technology, and points out several aspects of the TMA construction and its applications for clinical research.
Asunto(s)
Proteínas de Neoplasias/análisis , Neoplasias/genética , Neoplasias/patología , Análisis de Secuencia por Matrices de Oligonucleótidos/métodos , Bases de Datos Factuales , Amplificación de Genes , Expresión Génica , Inmunohistoquímica , Hibridación in Situ , Hibridación Fluorescente in Situ , Análisis de Secuencia por Matrices de Oligonucleótidos/tendencias , Adhesión en Parafina , Reproducibilidad de los ResultadosRESUMEN
Progress in the knowledge of molecular genetics and availability of high-throughput technologies offer the opportunity to identify new diagnostic and prognostic markers and new therapeutic targets in human cancer. The recently developed "tIssue microarrays" (TMA) technology allows parallel molecular profiling of clinical samples. Using this technique and immunohistochemistry (IHC), fluorescence in situ hybridisation (FISH), or RNA in situ hybridisation (ISH), the pathologist is now able to perform unprecedented large-scale analyses. The advantages are significant: large number of cases assessed simultaneously for numerous markers, processed in identical conditions, from reduced amount of archival tIssues, with an excellent correlation with standard methods, and a reduction in cost and time. This Article provides a short review of this technology, and points out several aspects of the TMA construction and its applications for clinical research.