Evaluation of a linear amplification method for small samples used on high-density oligonucleotide microarray analysis

High-density oligonucleotide microarray analysis has proven to be an excellent approach for gene expression profiling in human cancers. This technique assesses the expression of thousands of genes simultaneously, from at least 5 μg of total RNA per sample per experiment. This total RNA requirement poses a challenge when studying small, unique clinical samples, like biopsies. Recently, a new standardized protocol for small samples was released by Affymetrix, which includes a linear amplification step. To evaluate the impact of such amplification in the gene expression profiling of human ovarian cancer, we compared results obtained from 5 μg and 100 ng of total RNA from the same tumor sample, using the standard Affymetrix protocol and the new linear RNA amplification protocol, respectively. We identified a small bias in gene expression data caused by linear amplification, potentially due to shorter elongation products leading to misclassification of probe sets directed to the middle-<f>5′</f> region of the transcripts. Interestingly, the magnitude of the bias varied when different normalization and expression summary algorithms were used. However, this bias does not affect tumor gene expression profiling. Consequently, linear amplification may be of utility in cases of extremely low RNA recovery from critical and unique samples, such as small biopsies. [Copyright &y& Elsevier]