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Clinical and Genetic Predictive Models for the Prediction of Pathological Complete Response to Optimize the Effectiveness for Trastuzumab Based Chemotherapy
BACKGROUND: Trastuzumab shows excellent benefits for HER2+ breast cancer patients, although 20% treated remain unresponsive. We conducted a retrospective cohort study to optimize neoadjuvant chemotherapy and trastuzumab treatment in HER2+ breast cancer patients. METHODS: Six hundred patients were an...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8319743/ https://www.ncbi.nlm.nih.gov/pubmed/34336634 http://dx.doi.org/10.3389/fonc.2021.592393 |
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author | Li, Lun Chen, Min Zheng, Shuyue Li, Hanlu Chi, Weiru Xiu, Bingqiu Zhang, Qi Hou, Jianjing Wang, Jia Wu, Jiong |
author_facet | Li, Lun Chen, Min Zheng, Shuyue Li, Hanlu Chi, Weiru Xiu, Bingqiu Zhang, Qi Hou, Jianjing Wang, Jia Wu, Jiong |
author_sort | Li, Lun |
collection | PubMed |
description | BACKGROUND: Trastuzumab shows excellent benefits for HER2+ breast cancer patients, although 20% treated remain unresponsive. We conducted a retrospective cohort study to optimize neoadjuvant chemotherapy and trastuzumab treatment in HER2+ breast cancer patients. METHODS: Six hundred patients were analyzed to identify clinical characteristics of those not achieving a pathological complete response (pCR) to develop a clinical predictive model. Available RNA sequence data was also reviewed to develop a genetic model for pCR. RESULTS: The pCR rate was 39.8% and pCR was associated with superior disease free survival and overall survival. ER negativity and PR negativity, higher HER2 IHC scores, higher Ki-67, and trastuzumab use were associated with improved pCR. Weekly paclitaxel and carboplatin had the highest pCR rate (46.70%) and the anthracycline+taxanes regimen had the lowest rate (11.11%). Four published GEO datasets were analyzed and a 10-gene model and immune signature for pCR were developed. Non-pCR patients were ER(+)PR(+) and had a lower immune signature and gene model score. Hormone receptor status and immune signatures were independent predictive factors of pCR. CONCLUSION: Hormone receptor status and a 10-gene model could predict pCR independently and may be applied for patient selection and drug effectiveness optimization. |
format | Online Article Text |
id | pubmed-8319743 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-83197432021-07-30 Clinical and Genetic Predictive Models for the Prediction of Pathological Complete Response to Optimize the Effectiveness for Trastuzumab Based Chemotherapy Li, Lun Chen, Min Zheng, Shuyue Li, Hanlu Chi, Weiru Xiu, Bingqiu Zhang, Qi Hou, Jianjing Wang, Jia Wu, Jiong Front Oncol Oncology BACKGROUND: Trastuzumab shows excellent benefits for HER2+ breast cancer patients, although 20% treated remain unresponsive. We conducted a retrospective cohort study to optimize neoadjuvant chemotherapy and trastuzumab treatment in HER2+ breast cancer patients. METHODS: Six hundred patients were analyzed to identify clinical characteristics of those not achieving a pathological complete response (pCR) to develop a clinical predictive model. Available RNA sequence data was also reviewed to develop a genetic model for pCR. RESULTS: The pCR rate was 39.8% and pCR was associated with superior disease free survival and overall survival. ER negativity and PR negativity, higher HER2 IHC scores, higher Ki-67, and trastuzumab use were associated with improved pCR. Weekly paclitaxel and carboplatin had the highest pCR rate (46.70%) and the anthracycline+taxanes regimen had the lowest rate (11.11%). Four published GEO datasets were analyzed and a 10-gene model and immune signature for pCR were developed. Non-pCR patients were ER(+)PR(+) and had a lower immune signature and gene model score. Hormone receptor status and immune signatures were independent predictive factors of pCR. CONCLUSION: Hormone receptor status and a 10-gene model could predict pCR independently and may be applied for patient selection and drug effectiveness optimization. Frontiers Media S.A. 2021-07-15 /pmc/articles/PMC8319743/ /pubmed/34336634 http://dx.doi.org/10.3389/fonc.2021.592393 Text en Copyright © 2021 Li, Chen, Zheng, Li, Chi, Xiu, Zhang, Hou, Wang and Wu https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Li, Lun Chen, Min Zheng, Shuyue Li, Hanlu Chi, Weiru Xiu, Bingqiu Zhang, Qi Hou, Jianjing Wang, Jia Wu, Jiong Clinical and Genetic Predictive Models for the Prediction of Pathological Complete Response to Optimize the Effectiveness for Trastuzumab Based Chemotherapy |
title | Clinical and Genetic Predictive Models for the Prediction of Pathological Complete Response to Optimize the Effectiveness for Trastuzumab Based Chemotherapy |
title_full | Clinical and Genetic Predictive Models for the Prediction of Pathological Complete Response to Optimize the Effectiveness for Trastuzumab Based Chemotherapy |
title_fullStr | Clinical and Genetic Predictive Models for the Prediction of Pathological Complete Response to Optimize the Effectiveness for Trastuzumab Based Chemotherapy |
title_full_unstemmed | Clinical and Genetic Predictive Models for the Prediction of Pathological Complete Response to Optimize the Effectiveness for Trastuzumab Based Chemotherapy |
title_short | Clinical and Genetic Predictive Models for the Prediction of Pathological Complete Response to Optimize the Effectiveness for Trastuzumab Based Chemotherapy |
title_sort | clinical and genetic predictive models for the prediction of pathological complete response to optimize the effectiveness for trastuzumab based chemotherapy |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8319743/ https://www.ncbi.nlm.nih.gov/pubmed/34336634 http://dx.doi.org/10.3389/fonc.2021.592393 |
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