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Updated: Jul 14, 2026
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Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material
Published on: August 1, 2018
[Prognostic molecular classification of breast cancers based on gene expression profiling].
Yu-Mei Feng1, Xiao-Qing Li, Boo-Cun Sun
1Department of Biochemistry & Molecular Biology, Tianjin Cancer Hospital & Institute, Breast Cancer Prevention and Treatment Key Laboratory of Ministry of Education, Tianjin Medical University, Tianjing 21 300060, China.
Summary
This study identified gene markers that predict breast cancer metastasis and prognosis. These genes can classify patients into good or poor prognosis groups, aiding tailored therapy strategies.
Area of Science:
- Oncology
- Genomics
- Molecular Biology
Context:
- Breast cancer metastasis remains a significant challenge in patient outcomes.
- Accurate prognostic markers are crucial for effective treatment strategies.
- Gene expression profiling offers a powerful tool for identifying such markers.
Purpose:
- To identify gene expression profiles associated with distant metastasis in breast cancer.
- To develop a gene-based prognostic molecular classification system for breast cancer patients.
- To explore the clinical significance of identified gene markers.
Summary:
- Gene expression profiles of primary breast cancers with and without distant metastasis were compared using Oligo microarray hybridization.
- A set of 104 optimal genes was identified, capable of classifying patients into distinct prognostic groups.
- Genes involved in cell adhesion, migration, immune response, metabolism, and signal transduction showed significant differential expression.
Impact:
- The identified gene set accurately classifies breast cancer patients into "good" and "poor" prognosis groups.
- Patients with distant metastasis were predominantly classified into the "poor prognosis" group.
- This classification holds promise for guiding patient-tailored therapy strategies and improving breast cancer management.