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SET(ER/PR): a robust 18-gene predictor for sensitivity to endocrine therapy for metastatic breast cancer

There is a clinical need to predict sensitivity of metastatic hormone receptor-positive and HER2-negative (HR+/HER2−) breast cancer to endocrine therapy, and targeted RNA sequencing (RNAseq) offers diagnostic potential to measure both transcriptional activity and functional mutation. We developed th...

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Autores principales: Sinn, Bruno V., Fu, Chunxiao, Lau, Rosanna, Litton, Jennifer, Tsai, Tsung-Heng, Murthy, Rashmi, Tam, Alda, Andreopoulou, Eleni, Gong, Yun, Murthy, Ravi, Gould, Rebekah, Zhang, Ya, King, Tari A., Viale, Agnes, Andrade, Victor, Giri, Dilip, Salgado, Roberto, Laios, Ioanna, Sotiriou, Christos, Marginean, Esmeralda C., Kwiatkowski, Danielle N., Layman, Rachel M., Booser, Daniel, Hatzis, Christos, Vicente Valero, V., Fraser Symmans, W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6542807/
https://www.ncbi.nlm.nih.gov/pubmed/31231679
http://dx.doi.org/10.1038/s41523-019-0111-0
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author Sinn, Bruno V.
Fu, Chunxiao
Lau, Rosanna
Litton, Jennifer
Tsai, Tsung-Heng
Murthy, Rashmi
Tam, Alda
Andreopoulou, Eleni
Gong, Yun
Murthy, Ravi
Gould, Rebekah
Zhang, Ya
King, Tari A.
Viale, Agnes
Andrade, Victor
Giri, Dilip
Salgado, Roberto
Laios, Ioanna
Sotiriou, Christos
Marginean, Esmeralda C.
Kwiatkowski, Danielle N.
Layman, Rachel M.
Booser, Daniel
Hatzis, Christos
Vicente Valero, V.
Fraser Symmans, W.
author_facet Sinn, Bruno V.
Fu, Chunxiao
Lau, Rosanna
Litton, Jennifer
Tsai, Tsung-Heng
Murthy, Rashmi
Tam, Alda
Andreopoulou, Eleni
Gong, Yun
Murthy, Ravi
Gould, Rebekah
Zhang, Ya
King, Tari A.
Viale, Agnes
Andrade, Victor
Giri, Dilip
Salgado, Roberto
Laios, Ioanna
Sotiriou, Christos
Marginean, Esmeralda C.
Kwiatkowski, Danielle N.
Layman, Rachel M.
Booser, Daniel
Hatzis, Christos
Vicente Valero, V.
Fraser Symmans, W.
author_sort Sinn, Bruno V.
collection PubMed
description There is a clinical need to predict sensitivity of metastatic hormone receptor-positive and HER2-negative (HR+/HER2−) breast cancer to endocrine therapy, and targeted RNA sequencing (RNAseq) offers diagnostic potential to measure both transcriptional activity and functional mutation. We developed the SET(ER/PR) index to measure gene expression microarray probe sets that were correlated with hormone receptors (ESR1 and PGR) and robust to preanalytical and analytical influences. We tested SET(ER/PR) index in biopsies of metastastic HR+/HER2− breast cancer against the treatment outcomes in 140 patients. Then we customized the SET(ER/PR) assay to measure 18 informative, 10 reference transcripts, and sequence the ligand-binding domain (LBD) of ESR1 using droplet-based targeted RNAseq, and tested that in residual RNA from 53 patients. Higher SET(ER/PR) index in metastatic samples predicted longer PFS and OS when patients received endocrine therapy as next treatment, even after adjustment for clinical-pathologic risk factors (PFS: HR 0.534, 95% CI 0.299 to 0.955, p = 0.035; OS: HR 0.315, 95% CI 0.157 to 0.631, p = 0.001). Mutated ESR1 LBD was detected in 8/53 (15%) of metastases, involving 1−98% of ESR1 transcripts (all had high SET(ER/PR) index). A signature based on probe sets with good preanalytical and analytical performance facilitated our customization of an accurate targeted RNAseq assay to measure both phenotype and genotype of ER-related transcription. Elevated SET(ER/PR) was associated with prolonged sensitivity to endocrine therapy in patients with metastatic HR+/HER2− breast cancer, especially in the absence of mutated ESR1 transcript.
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spelling pubmed-65428072019-06-21 SET(ER/PR): a robust 18-gene predictor for sensitivity to endocrine therapy for metastatic breast cancer Sinn, Bruno V. Fu, Chunxiao Lau, Rosanna Litton, Jennifer Tsai, Tsung-Heng Murthy, Rashmi Tam, Alda Andreopoulou, Eleni Gong, Yun Murthy, Ravi Gould, Rebekah Zhang, Ya King, Tari A. Viale, Agnes Andrade, Victor Giri, Dilip Salgado, Roberto Laios, Ioanna Sotiriou, Christos Marginean, Esmeralda C. Kwiatkowski, Danielle N. Layman, Rachel M. Booser, Daniel Hatzis, Christos Vicente Valero, V. Fraser Symmans, W. NPJ Breast Cancer Article There is a clinical need to predict sensitivity of metastatic hormone receptor-positive and HER2-negative (HR+/HER2−) breast cancer to endocrine therapy, and targeted RNA sequencing (RNAseq) offers diagnostic potential to measure both transcriptional activity and functional mutation. We developed the SET(ER/PR) index to measure gene expression microarray probe sets that were correlated with hormone receptors (ESR1 and PGR) and robust to preanalytical and analytical influences. We tested SET(ER/PR) index in biopsies of metastastic HR+/HER2− breast cancer against the treatment outcomes in 140 patients. Then we customized the SET(ER/PR) assay to measure 18 informative, 10 reference transcripts, and sequence the ligand-binding domain (LBD) of ESR1 using droplet-based targeted RNAseq, and tested that in residual RNA from 53 patients. Higher SET(ER/PR) index in metastatic samples predicted longer PFS and OS when patients received endocrine therapy as next treatment, even after adjustment for clinical-pathologic risk factors (PFS: HR 0.534, 95% CI 0.299 to 0.955, p = 0.035; OS: HR 0.315, 95% CI 0.157 to 0.631, p = 0.001). Mutated ESR1 LBD was detected in 8/53 (15%) of metastases, involving 1−98% of ESR1 transcripts (all had high SET(ER/PR) index). A signature based on probe sets with good preanalytical and analytical performance facilitated our customization of an accurate targeted RNAseq assay to measure both phenotype and genotype of ER-related transcription. Elevated SET(ER/PR) was associated with prolonged sensitivity to endocrine therapy in patients with metastatic HR+/HER2− breast cancer, especially in the absence of mutated ESR1 transcript. Nature Publishing Group UK 2019-05-30 /pmc/articles/PMC6542807/ /pubmed/31231679 http://dx.doi.org/10.1038/s41523-019-0111-0 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Sinn, Bruno V.
Fu, Chunxiao
Lau, Rosanna
Litton, Jennifer
Tsai, Tsung-Heng
Murthy, Rashmi
Tam, Alda
Andreopoulou, Eleni
Gong, Yun
Murthy, Ravi
Gould, Rebekah
Zhang, Ya
King, Tari A.
Viale, Agnes
Andrade, Victor
Giri, Dilip
Salgado, Roberto
Laios, Ioanna
Sotiriou, Christos
Marginean, Esmeralda C.
Kwiatkowski, Danielle N.
Layman, Rachel M.
Booser, Daniel
Hatzis, Christos
Vicente Valero, V.
Fraser Symmans, W.
SET(ER/PR): a robust 18-gene predictor for sensitivity to endocrine therapy for metastatic breast cancer
title SET(ER/PR): a robust 18-gene predictor for sensitivity to endocrine therapy for metastatic breast cancer
title_full SET(ER/PR): a robust 18-gene predictor for sensitivity to endocrine therapy for metastatic breast cancer
title_fullStr SET(ER/PR): a robust 18-gene predictor for sensitivity to endocrine therapy for metastatic breast cancer
title_full_unstemmed SET(ER/PR): a robust 18-gene predictor for sensitivity to endocrine therapy for metastatic breast cancer
title_short SET(ER/PR): a robust 18-gene predictor for sensitivity to endocrine therapy for metastatic breast cancer
title_sort set(er/pr): a robust 18-gene predictor for sensitivity to endocrine therapy for metastatic breast cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6542807/
https://www.ncbi.nlm.nih.gov/pubmed/31231679
http://dx.doi.org/10.1038/s41523-019-0111-0
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