Systematic Review: Gene Expression Profiling Assays in Early-Stage Breast Cancer

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   Figure 1. Technologies used for high-throughput gene expression analysis.

   A. Breast cancer tumors are sampled at the treatment location and shipped to the central laboratory doing the assay, where pathologic review is done to assess cancer cell contents, followed by RNA preparation and integrity evaluation. Suitable samples are used to quantify RNA levels, thus assessing gene expression. When a gene is expressed, the transcription complex copies its DNA sequence into complementary RNA transcripts that are translated into proteins. High-throughput gene expression analysis aims to quantify messenger RNA (mRNA) populations in a given tissue. B. DNA microarray is the molecular biology technique enabling gene expression analysis in MammaPrint. RNA is labeled with fluorescent dye and hybridized against thousands of different nucleotide sequences corresponding to different genes and arrayed on a solid surface (that is, a modified microscope glass slide). On hybridization, fluorescence emitted by single locations on the microarray is used to estimate gene expression levels. In MammaPrint, a 2-color design is used, and RNA expression is estimated as a relative ratio between the sample and a reference RNA. For each patient, triplicate measurements are obtained from 2 microarrays inverting the labeling scheme. C. Real-time reverse transcriptase polymerase chain reaction (PCR) is the enabling technology to assess gene expression in Oncotype DX and H/I. This technique is based on reverse transcription (RT) (see Glossary) of a specific mRNA into the complementary DNA (cDNA) molecule, which is used as a template in PCR. The production of double-stranded DNA is accompanied by emission of light, which is recorded throughout the process and correlates to the amount of DNA that is produced. The higher the initial amount of RNA, the earlier light is emitted during RT-PCR, a measurable difference that allows gene expression to be quantitated. D. Gene expression levels are mathematically transformed into indexes predicting disease recurrence.
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   Figure 2. Systematic search strategy and results.