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Updated: May 26, 2026
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Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material
Published on: August 1, 2018
Practical implications of gene-expression-based assays for breast oncologists
Aleix Prat1, Matthew J Ellis, Charles M Perou
1Department of Genetics and Pathology, Lineberger Comprehensive Cancer Center, University of North Carolina, 450 West Drive, Chapel Hill, NC 27599, USA.
Nature Reviews. Clinical Oncology
|December 7, 2011
Summary
Gene-expression profiling advances breast cancer understanding and clinical care. Gene-expression signatures predict survival and treatment response, aiding in new clinical assays and classifying breast cancer subtypes.
Area of Science:
- Oncology
- Genomics
- Biomarker Discovery
Background:
- Gene-expression profiling has significantly advanced breast cancer biology and clinical care.
- Supervised and unsupervised analyses have yielded critical insights into breast cancer.
- This includes the identification of gene-expression signatures for predicting outcomes and classifying molecular subtypes.
Purpose of the Study:
- To review the clinical utility of gene-expression-based assays in breast cancer.
- To evaluate the technical potential of these assays as clinical tools.
- To compare their performance against current standard-of-care breast cancer biomarkers.
Main Methods:
- Review of scientific literature on gene-expression profiling in breast cancer.
- Analysis of supervised and unsupervised statistical approaches.
- Comparison of gene-expression signatures with existing biomarkers.
Main Results:
- Supervised analyses have produced gene-expression signatures for predicting survival and treatment response.
- Unsupervised analyses have identified biological signatures, including the 'intrinsic' molecular subtypes of breast cancer.
- These subtypes enhance the understanding of breast cancer heterogeneity and potential clinical utility.
Conclusions:
- Gene-expression profiling offers significant advancements in understanding breast cancer heterogeneity.
- Gene-expression-based assays show promise as clinical tools for diagnosis and treatment selection.
- Further evaluation is needed to establish their performance relative to current standard biomarkers.
