Cargando…

A Qualitative Transcriptional Signature for Predicting Extreme Resistance of ER-Negative Breast Cancer to Paclitaxel, Doxorubicin, and Cyclophosphamide Neoadjuvant Chemotherapy

For estrogen receptor (ER)-negative breast cancer patients, paclitaxel (P), doxorubicin (A) and cyclophosphamide (C) neoadjuvant chemotherapy (NAC) is the standard therapeutic regimen. Pathologic complete response (pCR) and residual disease (RD) are common surrogate measures of chemosensitivity. Aft...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Yanhua, Cai, Hao, Chen, Wannan, Guan, Qingzhou, He, Jun, Guo, Zheng, Li, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7109260/
https://www.ncbi.nlm.nih.gov/pubmed/32269999
http://dx.doi.org/10.3389/fmolb.2020.00034
_version_ 1783512916158316544
author Chen, Yanhua
Cai, Hao
Chen, Wannan
Guan, Qingzhou
He, Jun
Guo, Zheng
Li, Jing
author_facet Chen, Yanhua
Cai, Hao
Chen, Wannan
Guan, Qingzhou
He, Jun
Guo, Zheng
Li, Jing
author_sort Chen, Yanhua
collection PubMed
description For estrogen receptor (ER)-negative breast cancer patients, paclitaxel (P), doxorubicin (A) and cyclophosphamide (C) neoadjuvant chemotherapy (NAC) is the standard therapeutic regimen. Pathologic complete response (pCR) and residual disease (RD) are common surrogate measures of chemosensitivity. After NAC, most patients still have RD; of these, some partially respond to NAC, whereas others show extreme resistance and cannot benefit from NAC but only suffer complications resulting from drug toxicity. Here we developed a qualitative transcriptional signature, based on the within-sample relative expression ordering (REO) of gene pairs, to identify extremely resistant samples to PAC NAC. Using gene expression data for ER-negative breast cancer patients including 113 pCR samples and 137 RD samples from four datasets, we selected 61 gene pairs with reversal REO patterns between the two groups as the resistance signature, denoted as NR61. Samples with more than 37 signature gene pairs that had the same REO patterns within the extremely resistant group were defined as having extreme resistance; otherwise, they were considered responders. In the GSE25055 and GSE25065 dataset, the NR61 signature could correctly identify 44 (97.8%) of the 45 pCR samples and 22 (95.7%) of the 23 pCR samples as responder samples, respectively; it also identified 13 (16.9%) of 77 RD samples and 8 (21.1%) of 38 RD samples as extremely resistant samples, respectively. Survival analysis showed that the distant relapse-free survival (DRFS) time of the 14 extremely resistant cases was significantly shorter than that of the 108 responders (P < 0.01; HR = 3.84; 95% CI = 1.91–7.70) in GSE25055. Similar results were obtained in GSE25065. Moreover, in the integrated data of the two datasets with 94 responders and 21 extremely resistant samples identified from RD patients, the former had significantly longer DRFS than the latter (P < 0.01; HR = 2.22; 95% CI = 1.26–3.90). In summary, our signature could effectively identify patients who completely respond to PAC NAC, as well as cases of extreme resistance, which can assist decision-making on the clinical therapy for these patients.
format Online
Article
Text
id pubmed-7109260
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-71092602020-04-08 A Qualitative Transcriptional Signature for Predicting Extreme Resistance of ER-Negative Breast Cancer to Paclitaxel, Doxorubicin, and Cyclophosphamide Neoadjuvant Chemotherapy Chen, Yanhua Cai, Hao Chen, Wannan Guan, Qingzhou He, Jun Guo, Zheng Li, Jing Front Mol Biosci Molecular Biosciences For estrogen receptor (ER)-negative breast cancer patients, paclitaxel (P), doxorubicin (A) and cyclophosphamide (C) neoadjuvant chemotherapy (NAC) is the standard therapeutic regimen. Pathologic complete response (pCR) and residual disease (RD) are common surrogate measures of chemosensitivity. After NAC, most patients still have RD; of these, some partially respond to NAC, whereas others show extreme resistance and cannot benefit from NAC but only suffer complications resulting from drug toxicity. Here we developed a qualitative transcriptional signature, based on the within-sample relative expression ordering (REO) of gene pairs, to identify extremely resistant samples to PAC NAC. Using gene expression data for ER-negative breast cancer patients including 113 pCR samples and 137 RD samples from four datasets, we selected 61 gene pairs with reversal REO patterns between the two groups as the resistance signature, denoted as NR61. Samples with more than 37 signature gene pairs that had the same REO patterns within the extremely resistant group were defined as having extreme resistance; otherwise, they were considered responders. In the GSE25055 and GSE25065 dataset, the NR61 signature could correctly identify 44 (97.8%) of the 45 pCR samples and 22 (95.7%) of the 23 pCR samples as responder samples, respectively; it also identified 13 (16.9%) of 77 RD samples and 8 (21.1%) of 38 RD samples as extremely resistant samples, respectively. Survival analysis showed that the distant relapse-free survival (DRFS) time of the 14 extremely resistant cases was significantly shorter than that of the 108 responders (P < 0.01; HR = 3.84; 95% CI = 1.91–7.70) in GSE25055. Similar results were obtained in GSE25065. Moreover, in the integrated data of the two datasets with 94 responders and 21 extremely resistant samples identified from RD patients, the former had significantly longer DRFS than the latter (P < 0.01; HR = 2.22; 95% CI = 1.26–3.90). In summary, our signature could effectively identify patients who completely respond to PAC NAC, as well as cases of extreme resistance, which can assist decision-making on the clinical therapy for these patients. Frontiers Media S.A. 2020-03-25 /pmc/articles/PMC7109260/ /pubmed/32269999 http://dx.doi.org/10.3389/fmolb.2020.00034 Text en Copyright © 2020 Chen, Cai, Chen, Guan, He, Guo and Li. http://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 Molecular Biosciences
Chen, Yanhua
Cai, Hao
Chen, Wannan
Guan, Qingzhou
He, Jun
Guo, Zheng
Li, Jing
A Qualitative Transcriptional Signature for Predicting Extreme Resistance of ER-Negative Breast Cancer to Paclitaxel, Doxorubicin, and Cyclophosphamide Neoadjuvant Chemotherapy
title A Qualitative Transcriptional Signature for Predicting Extreme Resistance of ER-Negative Breast Cancer to Paclitaxel, Doxorubicin, and Cyclophosphamide Neoadjuvant Chemotherapy
title_full A Qualitative Transcriptional Signature for Predicting Extreme Resistance of ER-Negative Breast Cancer to Paclitaxel, Doxorubicin, and Cyclophosphamide Neoadjuvant Chemotherapy
title_fullStr A Qualitative Transcriptional Signature for Predicting Extreme Resistance of ER-Negative Breast Cancer to Paclitaxel, Doxorubicin, and Cyclophosphamide Neoadjuvant Chemotherapy
title_full_unstemmed A Qualitative Transcriptional Signature for Predicting Extreme Resistance of ER-Negative Breast Cancer to Paclitaxel, Doxorubicin, and Cyclophosphamide Neoadjuvant Chemotherapy
title_short A Qualitative Transcriptional Signature for Predicting Extreme Resistance of ER-Negative Breast Cancer to Paclitaxel, Doxorubicin, and Cyclophosphamide Neoadjuvant Chemotherapy
title_sort qualitative transcriptional signature for predicting extreme resistance of er-negative breast cancer to paclitaxel, doxorubicin, and cyclophosphamide neoadjuvant chemotherapy
topic Molecular Biosciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7109260/
https://www.ncbi.nlm.nih.gov/pubmed/32269999
http://dx.doi.org/10.3389/fmolb.2020.00034
work_keys_str_mv AT chenyanhua aqualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy
AT caihao aqualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy
AT chenwannan aqualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy
AT guanqingzhou aqualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy
AT hejun aqualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy
AT guozheng aqualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy
AT lijing aqualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy
AT chenyanhua qualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy
AT caihao qualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy
AT chenwannan qualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy
AT guanqingzhou qualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy
AT hejun qualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy
AT guozheng qualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy
AT lijing qualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy