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Updated: Mar 11, 2026

Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material
Published on: August 1, 2018
[A Review Multigene Assays for Clinical Utility in Breast Cancer]
Kazuhiro Araki1, Yoshinori Ito
1Dept. of Breast Medical Oncology, The Cancer Institute Hospital Ariake, The Japanese Foundation for Cancer Research.
Abstract:
Multigene assays that simultaneously measure the expression of various breast cancer genes have been developed to guide the use of adjuvant chemotherapy in early breast cancer. The efficacy of adjuvant therapies depends on the recurrence risk for an individual patient. As a result, accurate prediction of the recurrence risk is vital for precise adjuvant chemotherapy in individual breast cancer patients. The recurrence risk as typically assessed by conventional examination of histological data of immuno-histological biomarkers(ER, PR, HER2, and Ki-67)is not sufficient to select subsets of patients. Therefore, validated gene expression signatures are useful, in addition to well-established clinico-pathological factors. Available gene expression assay systems, such as MammaPrint®, Oncotype DX®, PAM50 ROR, GGI, EndoPredict®(EP), Breast Cancer IndexSM(BCI), and Curebest®95GC Breast, are recommended. While MammaPrint®and Oncotype DX®are the most predictive of the recurrence risk within the first 5 years of diagnosis, BCI and EPclin have demonstrated utility in predicting late recurrence. In addition, PAM50 provides further biological insights by classifying breast cancers into intrinsic molecular subtypes. These gene expression signatures have become important tools in clinical practice for the identification of low-risk endocrine-positive patients in whom chemotherapy could be avoided. However, there is much work left in the development of a molecular classification considering the biology and novel therapeutic targets in high-risk recurrent disease because chemotherapy has only modest benefits in this population. The recognition of genomic mutations and their relationship to a patient's responsiveness to various therapies will provide important breakthroughs toward precision medicine.
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