Comparison of gene expression profiling by reverse transcription quantitative PCR between fresh frozen and formalin-fixed, paraffin-embedded breast cancer tissues

Author:

Sánchez-Navarro Iker1,Gámez-Pozo Angelo1,González-Barón Manuel2,Pinto-Marín Álvaro2,Hardisson David3,López Rocío1,Madero Rosario4,Cejas Paloma1,Mendiola Marta13,Espinosa Enrique2,Vara Juan Ángel Fresno1

Affiliation:

1. Laboratory of Molecular Pathology and Oncology, Research Unit, Hospital Universitario La Paz, Madrid, Spain

2. Department of Medical Oncology, Hospital Universitario La Paz, Madrid, Spain

3. Department of Pathology, Hospital Universitario La Paz, Madrid, Spain

4. Biostatistics Unit, Hospital Universitario La Paz, Madrid, Spain

Abstract

Recent reports demonstrate the feasibility of quantifying gene expression by using RNA isolated from blocks of formalin-fixed, paraffin-embedded (FFPE) tumor tissue. The development of molecular tests for clinical use based on archival materials would be of great utility in the search for and validation of important genes or gene expression profiles. In this study, we compared the performance of different normalization strategies in the correlation of quantitative data between fresh frozen (FF) and FFPE samples and analyzed the parameters that characterize such correlation for each gene. Total RNA extracted from FFPE samples presented a shift in raw cycle threshold (Cq) values that can be explained by its extensive degradation. Proper normalization can compensate for the effects of RNA degradation in gene expression measurements. We show that correlation between normalized expression values is better for moderately to highly expressed genes whose expression varies significantly between samples. Nevertheless, some genes had no correlation. These genes should not be included in molecular tests for clinical use based on FFPE samples. Our results could serve as a guide when developing clinical diagnostic tests based on RT-qPCR analyses of FFPE tissues in the coming era of treatment decision-making based on gene expression profiling.

Publisher

Future Science Ltd

Subject

General Biochemistry, Genetics and Molecular Biology,Biotechnology

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