Converting a breast cancer microarray signature into a high-throughput diagnostic test
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Open Access
- 30 October 2006
- journal article
- Published by Springer Nature in BMC Genomics
- Vol. 7 (1) , 278
- https://doi.org/10.1186/1471-2164-7-278
Abstract
A 70-gene tumor expression profile was established as a powerful predictor of disease outcome in young breast cancer patients. This profile, however, was generated on microarrays containing 25,000 60-mer oligonucleotides that are not designed for processing of many samples on a routine basis. To facilitate its use in a diagnostic setting, the 70-gene prognosis profile was translated into a customized microarray (MammaPrint) containing a reduced set of 1,900 probes suitable for high throughput processing. RNA of 162 patient samples from two previous studies was subjected to hybridization to this custom array to validate the prognostic value. Classification results obtained from the original analysis were then compared to those generated using the algorithms based on the custom microarray and showed an extremely high correlation of prognosis prediction between the original data and those generated using the custom mini-array (p < 0.0001). In this report we demonstrate for the first time that microarray technology can be used as a reliable diagnostic tool. The data clearly demonstrate the reproducibility and robustness of the small custom-made microarray. The array is therefore an excellent tool to predict outcome of disease in breast cancer patients.Keywords
This publication has 26 references indexed in Scilit:
- Validation and Clinical Utility of a 70-Gene Prognostic Signature for Women With Node-Negative Breast CancerJNCI Journal of the National Cancer Institute, 2006
- Changes in Gene Expression Associated With Response to Neoadjuvant Chemotherapy in Breast CancerJournal of Clinical Oncology, 2005
- Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancerThe Lancet, 2005
- Gene expression profiling in follicular lymphoma to assess clinical aggressiveness and to guide the choice of treatmentBlood, 2005
- A Gene-Expression Signature as a Predictor of Survival in Breast CancerNew England Journal of Medicine, 2002
- Gene expression profiling predicts clinical outcome of breast cancerNature, 2002
- Prediction of central nervous system embryonal tumour outcome based on gene expressionNature, 2002
- Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implicationsProceedings of the National Academy of Sciences, 2001
- Functional Discovery via a Compendium of Expression ProfilesCell, 2000
- Distinct types of diffuse large B-cell lymphoma identified by gene expression profilingNature, 2000