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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...

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Autores principales: Li, Lun, Chen, Min, Zheng, Shuyue, Li, Hanlu, Chi, Weiru, Xiu, Bingqiu, Zhang, Qi, Hou, Jianjing, Wang, Jia, Wu, Jiong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
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.
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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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