GeneChip™ Hybridization, Wash, and Stain Kit

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Hybridization controls like the Control Oligonucleotide B2 should be included

Upstream tips
Hybridization controls like the Control Oligonucleotide B2 should be included

Publication protocol

Gene expression analysis was conducted using Affymetrix Rat Genome 230 2.0 GeneChip® arrays (Affymetrix, Santa Clara, CA). One hundred ng of total RNA was amplified as directed in the Affymetrix 3’ IVT Express kit protocol. 12.5µg of amplified biotin-aRNAs were fragmented and 10µg were hybridized to each array for 16 hours at 45°C in a rotating hybridization oven using the Affymetrix Eukaryotic Target Hybridization Controls and protocol. Array slides were stained with streptavidin/phycoerythrin utilizing a double-antibody staining procedure and then washed for antibody amplification according to the GeneChip Hybridization, Wash and Stain Kit and user manual. Arrays were scanned in an Affymetrix Scanner 3000 and data was obtained using the GeneChip® Command Console Software (AGCC; Version 1.1) using the MAS5 algorithm to generate .CHP files.

Probe intensity data from all arrays were entered into the R software environment (http://www.R-project.org) directly from .cel files using the R/affy package (Gautier et al. 2003). Data quality was assessed using image reconstruction, intensity histograms and boxplots. Normalization was performed across all 11 samples (6 Fred-PE and 5 spontaneous mesothelioma samples) using the robust multiarray average (RMA) method to form one expression measure for each gene on each array (Irizarry et al. 2003). The RMA method adjusts the background of perfect match (PM) probes, applies a quantile normalization of the corrected PM values, and calculates final expression measures using the Tukey median polish algorithm. Treatment groups (cultured mesothelial cells (Fred-PE), spontaneous mesothelioma) were compared using a t-statistic whose null distribution was derived using 10,000 bootstrap samples by resampling the residuals (Efron and Tibshirani 1993). The bootstrap methodology was implemented in the ORIOGEN software package (Peddada et al. 2005). We applied Benjamini-Hochberg procedure (Benjamini and Hochberg 1995) for multiple testing with a nominal FDR of 0.01 to determine differential gene expression.

Core analysis of differentially expressed genes was conducted to determine biologic functions, canonical pathways, and transcription factor activation and over-represented classifications of genes were determined from statistical outcomes by testing for association with gene product relationships from a curated database of biological networks (Ingenuity Pathways Analysis™ (IPA) version 9.0) (www.ingenuity.com). The Ingenuity Pathways Knowledge Base (IPKB) consists of data with known biological relationships between genes and gene products. The significantly differentially expressed genes (p<0.001) in the IPA core analysis were then grouped by pathways to account for upstream and downstream players as well as overlapping pathways. Upstream activation (formerly known as transcription factor activation in earlier versions of IPA) was based on IPA z scores >2.0 with no bias.

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