Multiple gene expression analyses in human lymphoid tissues by TaqMan low-density array using amplified RNA isolated from paraffin-embedded samples

Annunziata Gloghini, Barbara Canal, Luigino Dal Maso, Antonino Carbone

Research output: Contribution to journalArticlepeer-review

Abstract

In this study, we examined whether small amounts of RNA available from fixed and paraffin-embedded samples could be increased and quantified while conserving the gene expression profile. To this aim, RNA was extracted by a modified version of an earlier described method and was amplified with a linear amplification system. Furthermore, using TaqMan low-density arrays technology, the expression of multiple genes was correlated in matched snap-frozen and paraffin-embedded tissues. The entire technical procedure was assessed on 7 reactive lymph nodes. The results of the study showed that highly degraded RNA could be amplified to a mean of a 1200 to 3500-fold increase. Furthermore, the amount of cDNA and the polymerase chain reaction amplification efficiency was higher in amplified RNA than in unamplified RNA (89% vs. 82%). The analysis of Ct and ΔCt values showed strong correlations in matched amplified versus unamplified, fixed and frozen samples, thus demonstrating the conservation of gene expression in amplified RNA. We conclude that small amounts of RNA from paraffin-embedded tissues can be successfully amplified without altering the gene expression. Consequently, TaqMan low-density array technology could be used successfully for the analysis of archival fixed and paraffin-embedded lymphoid tissue.

Original languageEnglish
Pages (from-to)156-164
Number of pages9
JournalDiagnostic Molecular Pathology
Volume18
Issue number3
DOIs
Publication statusPublished - Sep 2009

Keywords

  • Bouin-fixed tissues
  • Multiple gene expression analysis
  • Paraffin-embedded tissues
  • RNA amplification
  • RNA isolation
  • TaqMan low-density array

ASJC Scopus subject areas

  • Pathology and Forensic Medicine
  • Cell Biology
  • Molecular Biology

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