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The E2F4 prognostic signature predicts pathological response to neoadjuvant chemotherapy in breast cancer patients
BACKGROUND: Neoadjuvant chemotherapy is a key component of breast cancer treatment regimens and pathologic complete response to this therapy varies among patients. This is presumably due to differences in the molecular mechanisms that underlie each tumor’s disease pathology. Developing genomic clini...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5414335/ https://www.ncbi.nlm.nih.gov/pubmed/28464832 http://dx.doi.org/10.1186/s12885-017-3297-2 |
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author | Mark, Kenneth M. K. Varn, Frederick S. Ung, Matthew H. Qian, Feng Cheng, Chao |
author_facet | Mark, Kenneth M. K. Varn, Frederick S. Ung, Matthew H. Qian, Feng Cheng, Chao |
author_sort | Mark, Kenneth M. K. |
collection | PubMed |
description | BACKGROUND: Neoadjuvant chemotherapy is a key component of breast cancer treatment regimens and pathologic complete response to this therapy varies among patients. This is presumably due to differences in the molecular mechanisms that underlie each tumor’s disease pathology. Developing genomic clinical assays that accurately categorize responders from non-responders can provide patients with the most effective therapy for their individual disease. METHODS: We applied our previously developed E2F4 genomic signature to predict neoadjuvant chemotherapy response in breast cancer. E2F4 individual regulatory activity scores were calculated for 1129 patient samples across 5 independent breast cancer neoadjuvant chemotherapy datasets. Accuracy of the E2F4 signature in predicting neoadjuvant chemotherapy response was compared to that of the Oncotype DX and MammaPrint predictive signatures. RESULTS: In all datasets, E2F4 activity level was an accurate predictor of neoadjuvant chemotherapy response, with high E2F4 scores predictive of achieving pathologic complete response and low scores predictive of residual disease. These results remained significant even after stratifying patients by estrogen receptor (ER) status, tumor stage, and breast cancer molecular subtypes. Compared to the Oncotype DX and MammaPrint signatures, our E2F4 signature achieved similar performance in predicting neoadjuvant chemotherapy response, though all signatures performed better in ER+ tumors compared to ER- ones. The accuracy of our signature was reproducible across datasets and was maintained when refined from a 199-gene signature down to a clinic-friendly 33-gene panel. CONCLUSION: Overall, we show that our E2F4 signature is accurate in predicting patient response to neoadjuvant chemotherapy. As this signature is more refined and comparable in performance to other clinically available gene expression assays in the prediction of neoadjuvant chemotherapy response, it should be considered when evaluating potential treatment options. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12885-017-3297-2) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5414335 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-54143352017-05-03 The E2F4 prognostic signature predicts pathological response to neoadjuvant chemotherapy in breast cancer patients Mark, Kenneth M. K. Varn, Frederick S. Ung, Matthew H. Qian, Feng Cheng, Chao BMC Cancer Research Article BACKGROUND: Neoadjuvant chemotherapy is a key component of breast cancer treatment regimens and pathologic complete response to this therapy varies among patients. This is presumably due to differences in the molecular mechanisms that underlie each tumor’s disease pathology. Developing genomic clinical assays that accurately categorize responders from non-responders can provide patients with the most effective therapy for their individual disease. METHODS: We applied our previously developed E2F4 genomic signature to predict neoadjuvant chemotherapy response in breast cancer. E2F4 individual regulatory activity scores were calculated for 1129 patient samples across 5 independent breast cancer neoadjuvant chemotherapy datasets. Accuracy of the E2F4 signature in predicting neoadjuvant chemotherapy response was compared to that of the Oncotype DX and MammaPrint predictive signatures. RESULTS: In all datasets, E2F4 activity level was an accurate predictor of neoadjuvant chemotherapy response, with high E2F4 scores predictive of achieving pathologic complete response and low scores predictive of residual disease. These results remained significant even after stratifying patients by estrogen receptor (ER) status, tumor stage, and breast cancer molecular subtypes. Compared to the Oncotype DX and MammaPrint signatures, our E2F4 signature achieved similar performance in predicting neoadjuvant chemotherapy response, though all signatures performed better in ER+ tumors compared to ER- ones. The accuracy of our signature was reproducible across datasets and was maintained when refined from a 199-gene signature down to a clinic-friendly 33-gene panel. CONCLUSION: Overall, we show that our E2F4 signature is accurate in predicting patient response to neoadjuvant chemotherapy. As this signature is more refined and comparable in performance to other clinically available gene expression assays in the prediction of neoadjuvant chemotherapy response, it should be considered when evaluating potential treatment options. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12885-017-3297-2) contains supplementary material, which is available to authorized users. BioMed Central 2017-05-02 /pmc/articles/PMC5414335/ /pubmed/28464832 http://dx.doi.org/10.1186/s12885-017-3297-2 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Mark, Kenneth M. K. Varn, Frederick S. Ung, Matthew H. Qian, Feng Cheng, Chao The E2F4 prognostic signature predicts pathological response to neoadjuvant chemotherapy in breast cancer patients |
title | The E2F4 prognostic signature predicts pathological response to neoadjuvant chemotherapy in breast cancer patients |
title_full | The E2F4 prognostic signature predicts pathological response to neoadjuvant chemotherapy in breast cancer patients |
title_fullStr | The E2F4 prognostic signature predicts pathological response to neoadjuvant chemotherapy in breast cancer patients |
title_full_unstemmed | The E2F4 prognostic signature predicts pathological response to neoadjuvant chemotherapy in breast cancer patients |
title_short | The E2F4 prognostic signature predicts pathological response to neoadjuvant chemotherapy in breast cancer patients |
title_sort | e2f4 prognostic signature predicts pathological response to neoadjuvant chemotherapy in breast cancer patients |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5414335/ https://www.ncbi.nlm.nih.gov/pubmed/28464832 http://dx.doi.org/10.1186/s12885-017-3297-2 |
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