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...
Main Authors: | , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2020-03-01
|
Series: | Frontiers in Molecular Biosciences |
Subjects: | |
Online Access: | https://www.frontiersin.org/article/10.3389/fmolb.2020.00034/full |
id |
doaj-ecd7c950521d411085b53a6181cb1c9b |
---|---|
record_format |
Article |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yanhua Chen Yanhua Chen Hao Cai Wannan Chen Wannan Chen Qingzhou Guan Qingzhou Guan Qingzhou Guan Jun He Jun He Zheng Guo Zheng Guo Jing Li Jing Li |
spellingShingle |
Yanhua Chen Yanhua Chen Hao Cai Wannan Chen Wannan Chen Qingzhou Guan Qingzhou Guan Qingzhou Guan Jun He Jun He Zheng Guo Zheng Guo Jing Li Jing Li A Qualitative Transcriptional Signature for Predicting Extreme Resistance of ER-Negative Breast Cancer to Paclitaxel, Doxorubicin, and Cyclophosphamide Neoadjuvant Chemotherapy Frontiers in Molecular Biosciences breast cancer neoadjuvant chemotherapy pathological complete response extreme resistance relative expression ordering |
author_facet |
Yanhua Chen Yanhua Chen Hao Cai Wannan Chen Wannan Chen Qingzhou Guan Qingzhou Guan Qingzhou Guan Jun He Jun He Zheng Guo Zheng Guo Jing Li Jing Li |
author_sort |
Yanhua Chen |
title |
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_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_sort |
qualitative transcriptional signature for predicting extreme resistance of er-negative breast cancer to paclitaxel, doxorubicin, and cyclophosphamide neoadjuvant chemotherapy |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Molecular Biosciences |
issn |
2296-889X |
publishDate |
2020-03-01 |
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. |
topic |
breast cancer neoadjuvant chemotherapy pathological complete response extreme resistance relative expression ordering |
url |
https://www.frontiersin.org/article/10.3389/fmolb.2020.00034/full |
work_keys_str_mv |
AT yanhuachen aqualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT yanhuachen aqualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT haocai aqualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT wannanchen aqualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT wannanchen aqualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT qingzhouguan aqualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT qingzhouguan aqualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT qingzhouguan aqualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT junhe aqualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT junhe aqualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT zhengguo aqualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT zhengguo aqualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT jingli aqualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT jingli aqualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT yanhuachen qualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT yanhuachen qualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT haocai qualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT wannanchen qualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT wannanchen qualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT qingzhouguan qualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT qingzhouguan qualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT qingzhouguan qualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT junhe qualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT junhe qualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT zhengguo qualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT zhengguo qualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT jingli qualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy AT jingli qualitativetranscriptionalsignatureforpredictingextremeresistanceofernegativebreastcancertopaclitaxeldoxorubicinandcyclophosphamideneoadjuvantchemotherapy |
_version_ |
1724790666601431040 |
spelling |
doaj-ecd7c950521d411085b53a6181cb1c9b2020-11-25T02:38:29ZengFrontiers Media S.A.Frontiers in Molecular Biosciences2296-889X2020-03-01710.3389/fmolb.2020.00034509622A Qualitative Transcriptional Signature for Predicting Extreme Resistance of ER-Negative Breast Cancer to Paclitaxel, Doxorubicin, and Cyclophosphamide Neoadjuvant ChemotherapyYanhua Chen0Yanhua Chen1Hao Cai2Wannan Chen3Wannan Chen4Qingzhou Guan5Qingzhou Guan6Qingzhou Guan7Jun He8Jun He9Zheng Guo10Zheng Guo11Jing Li12Jing Li13Fujian Key Laboratory of Medical Bioinformatics, Department of Bioinformatics, The School of Basic Medical Sciences, Fujian Medical University, Fuzhou, ChinaKey Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, ChinaMedical Big Data and Bioinformatics Research Center, First Affiliated Hospital of Gannan Medical University, Ganzhou, ChinaKey Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, ChinaFujian Key Laboratory of Tumor Microbiology, Department of Medical Microbiology, Fujian Medical University, Fuzhou, ChinaHenan Key Laboratory of Chinese Medicine for Respiratory Disease, Henan University of Chinese Medicine, Zhengzhou, ChinaCo-construction Collaborative Innovation Center for Chinese Medicine and Respiratory Diseases by Henan & Education Ministry of P.R. China, Henan University of Chinese Medicine, Zhengzhou, ChinaAcademy of Sciences of Chinese Medicine, Henan University of Chinese Medicine, Zhengzhou, ChinaFujian Key Laboratory of Medical Bioinformatics, Department of Bioinformatics, The School of Basic Medical Sciences, Fujian Medical University, Fuzhou, ChinaKey Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, ChinaFujian Key Laboratory of Medical Bioinformatics, Department of Bioinformatics, The School of Basic Medical Sciences, Fujian Medical University, Fuzhou, ChinaKey Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, ChinaFujian Key Laboratory of Medical Bioinformatics, Department of Bioinformatics, The School of Basic Medical Sciences, Fujian Medical University, Fuzhou, ChinaKey Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, ChinaFor 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.https://www.frontiersin.org/article/10.3389/fmolb.2020.00034/fullbreast cancerneoadjuvant chemotherapypathological complete responseextreme resistancerelative expression ordering |