1. From RNA isolation to microarray analysis: Comparison of methods in FFPE tissues
- Author
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Ozlem Ilk, Hilal Özdağ, Beyza Doğanay Erdoğan, Nevin Belder, Berna Savaş, Arzu Ensari, and Oznur Coskun
- Subjects
0301 basic medicine ,Tissue Fixation ,Computational biology ,Biology ,Bioinformatics ,Pathology and Forensic Medicine ,03 medical and health sciences ,0302 clinical medicine ,Formaldehyde ,Gene expression ,Humans ,Paraffin Embedding ,Microarray analysis techniques ,Gene Expression Profiling ,High-Throughput Nucleotide Sequencing ,RNA ,Cell Biology ,Gene expression profiling ,030104 developmental biology ,Tissue Array Analysis ,Trizol ,030220 oncology & carcinogenesis ,Nucleic acid ,Human genome ,RNA extraction - Abstract
Background Genome-wide gene expression profiling analysis of FFPE tissue samples is indispensable for cancer research and provides the opportunity to evaluate links between molecular and clinical information, however, working with FFPE samples is challenging due to extensive cross-linking, fragmentation and limited quantities of nucleic acid. Thus, processing of FFPE tissue samples from RNA extraction to microarray analysis still needs optimization. Materials and methods In this study, a modified deparaffinization protocol was conducted prior to RNA isolation. Trizol, Qiagen RNeasy FFPE and Arcturus PicoPure RNA Isolation kits were used in parallel to compare their impact on RNA isolation. We also evaluated the effect of two different cRNA/cDNA preparation and labeling protocols with two different array platforms (Affymetrix Human Genome U133 Plus 2.0 and U133_X3P) on the percentage of present calls. Results Our optimization study shows that the Qiagen RNeasy FFPE kit with modified deparaffinization step gives better results (RNA quantity and quality) than the other two isolation kits. The Ribo-SPIA protocol gave a significantly higher percentage of present calls than the 3′ IVT cDNA amplification and labeling system. However, no significant differences were found between the two array platforms. Conclusion Our study paves the way for future high-throughput transcriptional analysis by optimizing FFPE tissue sample processing from RNA isolation to microarray analysis.
- Published
- 2016