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Updated: Aug 18, 2026
Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Published on: November 3, 2013
Prediction of hormone sensitivity by DNA microarray
1Division of Endocrinology, Saitama Cancer Center Research Institute, 818 Komuro, Ina-machi, Saitama, 362-0806, Japan. h.shin@nifty.com
Abstract:
Endocrine-therapy continues to be extensively developed for treatment of breast cancer, and accurate therapeutic prediction of this hormone-associated cancer is strongly desired. Moreover, the role of estrogen and its receptor on the estrogen-dependent growth of breast cancer cells has not been clarified hitherto. Thus, to develop a new diagnostic tool for endocrine-therapy, and to address the molecular mechanism of estrogen-dependent breast carcinogenesis, we investigated the gene expression profile of estrogen-responsive genes in breast cancer using DNA microarray technique. We first comprehensively analyzed the profile of estrogen responsiveness among several estrogen receptor (ER)-positive cancer cell lines by a large-scale DNA microarray. Based on the obtained information, a total of 138 genes which showed high induction or repression of the expression by estrogen stimulation were selected and provided for custom microarray. The results of the custom microarray analysis were consistent with those of large-scale microarray analysis, and revealed that they were clearly categorized into early- or late-response types. Further analysis of these genes may provide new clues in the elucidation of the estrogen-dependent growth mechanisms of cancer. Furthermore, the custom microarray analysis of ER-positive breast cancer tissues also showed similar but not identical profiles to those of cell lines, indicating the potential of this custom microarray to predict the response to endocrine-therapy in the breast cancer. Moreover, in order to discover the new predictive factors for endocrine therapy in breast cancer patients, several candidate genes were selected and their expressions in breast cancer tissues were analyzed by real-time RT-PCR and by immunohistochemical technique. These studies could provide new clues for elucidation of the estrogen-dependent mechanisms of cancer and clinical benefit for patients.
Insights
This study explored estrogen-responsive genes in breast cancer using DNA microarrays to improve endocrine-therapy prediction. Findings reveal gene expression patterns that may enhance therapeutic strategies for hormone-associated breast cancer.
Area of Science:
- Oncology
- Molecular Biology
- Genomics
Background:
- Endocrine-therapy is crucial for breast cancer treatment, but accurate prediction remains a challenge.
- The precise role of estrogen and its receptor in estrogen-dependent breast cancer growth requires further elucidation.
- Developing novel diagnostic tools for endocrine-therapy is highly desired.
Purpose of the Study:
- To investigate the gene expression profile of estrogen-responsive genes in breast cancer using DNA microarray.
- To develop a new diagnostic tool for endocrine-therapy prediction.
- To address the molecular mechanisms of estrogen-dependent breast carcinogenesis.
Main Methods:
- Large-scale DNA microarray analysis of estrogen responsiveness in estrogen receptor (ER)-positive cancer cell lines.
- Selection of 138 estrogen-responsive genes for custom microarray analysis.
- Validation using real-time RT-PCR and immunohistochemical techniques on breast cancer tissues.
Main Results:
- Identified 138 key estrogen-responsive genes, categorized into early- and late-response types.
- Custom microarray analysis confirmed large-scale findings and revealed distinct profiles in ER-positive breast cancer tissues compared to cell lines.
- Candidate genes were identified with potential for predicting endocrine-therapy response.
Conclusions:
- Gene expression profiling offers insights into estrogen-dependent breast cancer growth mechanisms.
- The developed custom microarray shows potential for predicting endocrine-therapy response in breast cancer patients.
- Further research on identified genes may lead to improved clinical benefit and novel predictive factors for endocrine therapy.
