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Predicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen.

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Bibliographic Details
Title: Predicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen.
Authors: Loi, S., Haibe-Kains, B., Desmedt, C., Wirapati, P., Lallemand, F., Tutt, A.M., Gillet, C., Ellis, P., Ryder, K., Reid, J.F., Daidone, M.G., Pierotti, M.A., Berns, E.M., Jansen, M.P., Foekens, J.A., Delorenzi, M., Bontempi, G., Piccart, M.J., Sotiriou, C.
Publication Year: 2025
Collection: Université de Lausanne (UNIL): Serval - Serveur académique lausannois
Subject Terms: Antineoplastic Agents, Hormonal/therapeutic use, Breast Neoplasms/drug therapy, Breast Neoplasms/genetics, Chemotherapy, Adjuvant, Databases, Genetic, Female, Gene Expression Profiling/statistics & numerical data, Humans, Neoplasms, Hormone-Dependent/drug therapy, Hormone-Dependent/genetics, Prognosis, Receptors, Estrogen/metabolism, Progesterone/metabolism, Tamoxifen/therapeutic use
Description: Background: Estrogen receptor positive (ER+) breast cancers (BC) are heterogeneous with regard to their clinical behavior and response to therapies. The ER is currently the best predictor of response to the anti-estrogen agent tamoxifen, yet up to 30-40% of ER+ BC will relapse despite tamoxifen treatment. New prognostic biomarkers and further biological understanding of tamoxifen resistance are required. We used gene expression profiling to develop an outcome-based predictor using a training set of 255 ER+ BC samples from women treated with adjuvant tamoxifen monotherapy. We used clusters of highly correlated genes to develop our predictor to facilitate both signature stability and biological interpretation. Independent validation was performed using 362 tamoxifen-treated ER+ BC samples obtained from multiple institutions and treated with tamoxifen only in the adjuvant and metastatic settings.Results: We developed a gene classifier consisting of 181 genes belonging to 13 biological clusters. In the independent set of adjuvantly-treated samples, it was able to define two distinct prognostic groups (HR 2.01 95% CI: 1.29-3.13; p = 0.002). Six of the 13 gene clusters represented pathways involved in cell cycle and proliferation. In 112 metastatic breast cancer patients treated with tamoxifen, one of the classifier components suggesting a cellular inflammatory mechanism was significantly predictive of response.Conclusion: We have developed a gene classifier that can predict clinical outcome in tamoxifen-treated ER+ BC patients. Whilst our study emphasizes the important role of proliferation genes in prognosis, our approach proposes other genes and pathways that may elucidate further mechanisms that influence clinical outcome and prediction of response to tamoxifen.
Document Type: article in journal/newspaper
File Description: application/pdf
Language: English
ISSN: 1471-2164
Relation: BMC Genomics; https://iris.unil.ch/handle/iris/243228; serval:BIB_FAE9D819F981; 000256548700001
DOI: 10.1186/1471-2164-9-239
Availability: https://iris.unil.ch/handle/iris/243228
https://doi.org/10.1186/1471-2164-9-239
Accession Number: edsbas.5DEEA30E
Database: BASE
Description
Abstract:Background: Estrogen receptor positive (ER+) breast cancers (BC) are heterogeneous with regard to their clinical behavior and response to therapies. The ER is currently the best predictor of response to the anti-estrogen agent tamoxifen, yet up to 30-40% of ER+ BC will relapse despite tamoxifen treatment. New prognostic biomarkers and further biological understanding of tamoxifen resistance are required. We used gene expression profiling to develop an outcome-based predictor using a training set of 255 ER+ BC samples from women treated with adjuvant tamoxifen monotherapy. We used clusters of highly correlated genes to develop our predictor to facilitate both signature stability and biological interpretation. Independent validation was performed using 362 tamoxifen-treated ER+ BC samples obtained from multiple institutions and treated with tamoxifen only in the adjuvant and metastatic settings.Results: We developed a gene classifier consisting of 181 genes belonging to 13 biological clusters. In the independent set of adjuvantly-treated samples, it was able to define two distinct prognostic groups (HR 2.01 95% CI: 1.29-3.13; p = 0.002). Six of the 13 gene clusters represented pathways involved in cell cycle and proliferation. In 112 metastatic breast cancer patients treated with tamoxifen, one of the classifier components suggesting a cellular inflammatory mechanism was significantly predictive of response.Conclusion: We have developed a gene classifier that can predict clinical outcome in tamoxifen-treated ER+ BC patients. Whilst our study emphasizes the important role of proliferation genes in prognosis, our approach proposes other genes and pathways that may elucidate further mechanisms that influence clinical outcome and prediction of response to tamoxifen.
ISSN:14712164
DOI:10.1186/1471-2164-9-239