Gene Expression
Using Microarrays as Dependable Diagnostic Indicators for Breast Cancer
A review of Converting a breast cancer microarray signature into a high-throughput diagnostic test.
Note: This is a review of the published article listed below. All information, quotes, figures, methods, and findings mentioned in this review are from that article, and are the property of its authors and/or the publication in which the article originally appeared.
Although microarray technology has become a widely used tool for studying global gene expression, it is presently not used as a routine diagnostic tool. Glas and colleagues in The Netherlands (2006) describe the development of a customized diagnostic breast cancer mini-array, MammaPrint, based on the Amsterdam 70-gene expression profile, and describe its reliable use in a diagnostic setting. The custom MammaPrint was developed using Agilent’s multiplex, 8-pack mini-array, with eight identically printed regions or sub-arrays, each containing 1,900 60-mer oligonucleotide probes, including the 70 prognostic classifier genes, enabling eight individual hybridizations to be carried out simultaneously on a single microarray slide. To validate the prognostic value of the array, the researchers hybridized RNA from 162 patient samples used in two previous studies and compared results to those previously obtained to determine efficacy. Classification results showed an extremely high correlation of prognosis prediction between the original data and those generated using the custom mini-array. This work demonstrates for the first time that microarray technology can be used as a reliable and robust diagnostic tool for predicting the outcome of disease in breast cancer patients.
Figure 1. Custom-designed Agilent multiplex array.
MammaPrint 8-pack, a single 1" × 3" slide containing 8 mini-arrays with 1,900 60-mer oligonucleotide probes, allowing for eight individual hybridizations simultaneously. The samples are hybridized against a common breast cancer reference pool.
Figure 2. Expression data matrix of 70 prognostic markers genes from tumors of 78 breast cancer patients hybridized using the custom microarray.
Each row represents a tumor and each column a gene. Genes are ordered according to their original ordering. Tumors are ordered by their correlation to the average profile of the good prognosis group (middle panel). The metastases status for each patient is shown in the right panel. White indicates patients who developed metastases within 5 years after the initial diagnosis, black indicates patients who continued to be metastasis free for at least 5 years.
Figure 3. Comparison of current data to published values.
Correlation of the 70 genes from each tumor to the average expression profile of the good outcome patients is plotted. On the Y axis results from the customized 8-pack test is plotted and on the X axis results are plotted using published data from the original paper [6] using Xdev values.
Figure 4. Custom array outcome of replicate experiments.
Cosine correlation to the good prognosis template is plotted, and is highly similar between duplicate experiments.
Title: Converting a breast cancer microarray signature into a high-throughput diagnostic test.
Journal: BMC Genomics. 2006 Oct 30;7:278.
Authors: Glas AM, Floore A, Delahaye LJ, Witteveen AT, Pover RC, Bakx N, Lahti-Domenici JS, Bruinsma TJ, Warmoes MO, Bernards R, Wessels LF, Van't Veer LJ.
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