RESUMEN
Archived formalin-fixed, paraffin embedded (FFPE) tissues constitute a vast, well-annotated, but underexploited resource for the molecular study of cancer progression, largely because degradation, chemical modification, and cross-linking, render FFPE RNA a suboptimal substrate for conventional analytical methods. We report here a modified protocol for RNA extraction from FFPE tissues which maximized the success rate (with 100% of samples) in the expression profiling of a set of 60 breast cancer samples on the WG-DASL platform; yielding data of sufficient quality such that in hierarchical clustering (a) 12/12 (100%) replicates correctly identified their respective counterparts, with a high self-correlation (r = 0.979), and (b) the overall sample set grouped with high specificity into ER+ (38/40; 95%) and ER- (18/20; 90%) subtypes. These results indicate that a large fraction of decade-old FFPE samples, of diverse institutional origins and processing histories, can yield RNA suitable for gene expression profiling experiments.
Asunto(s)
Neoplasias de la Mama/metabolismo , Neoplasias de la Mama/patología , Perfilación de la Expresión Génica/métodos , Mama/patología , Análisis por Conglomerados , Estudios de Cohortes , Receptor alfa de Estrógeno/biosíntesis , Femenino , Formaldehído/farmacología , Humanos , Inmunohistoquímica/métodos , Adhesión en Parafina/métodos , ARN Neoplásico/metabolismo , Reacción en Cadena de la Polimerasa de Transcriptasa InversaRESUMEN
MicroRNAs are small (approximately 22 nt) RNAs that regulate gene expression and play important roles in both normal and disease physiology. The use of microarrays for global characterization of microRNA expression is becoming increasingly popular and has the potential to be a widely used and valuable research tool. However, microarray profiling of microRNA expression raises a number of data analytic challenges that must be addressed in order to obtain reliable results. We introduce here a universal reference microRNA reagent set as well as a series of nonhuman spiked-in synthetic microRNA controls, and demonstrate their use for quality control and between-array normalization of microRNA expression data. We also introduce diagnostic plots designed to assess and compare various normalization methods. We anticipate that the reagents and analytic approach presented here will be useful for improving the reliability of microRNA microarray experiments.