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Predictive miRNAs Patterns in Blood of Breast Cancer Patients Demonstrating Resistance Towards Neoadjuvant Chemotherapy

OBJECTIVE: The effect of chemotherapy in patients with breast cancer (BC) is uncertain. This study attempted to analyze serum microRNAs (miRNAs) in NAC resistant and sensitive BC patients and develop a miRNA-based nomogram model. To further help clinicians make treatment decisions for hormone recept...

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Autores principales: Fan, Jingjing, Tang, Yunjian, Wang, Kunming, Yang, Shu, Ma, Binlin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10427486/
https://www.ncbi.nlm.nih.gov/pubmed/37593370
http://dx.doi.org/10.2147/BCTT.S415080
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author Fan, Jingjing
Tang, Yunjian
Wang, Kunming
Yang, Shu
Ma, Binlin
author_facet Fan, Jingjing
Tang, Yunjian
Wang, Kunming
Yang, Shu
Ma, Binlin
author_sort Fan, Jingjing
collection PubMed
description OBJECTIVE: The effect of chemotherapy in patients with breast cancer (BC) is uncertain. This study attempted to analyze serum microRNAs (miRNAs) in NAC resistant and sensitive BC patients and develop a miRNA-based nomogram model. To further help clinicians make treatment decisions for hormone receptor-positive patients. METHODS: A total of 110 BC patients with NAC were recruited and assigned in sensitive and resistant group, and 4 sensitive patients and 3 resistant patients were subjected to high-throughput sequencing. The functions of their target genes were analyzed by GO and KEGG. Five BC-related reported miRNAs were selected for expression pattern measurement by RT-qPCR and multivariate logistic analysis. The nomogram model was developed using R 4.0.1, and its predictive efficacy, consistency and clinical application value in development and validation groups were evaluated using ROC, calibration and decision curves. RESULTS: There were 44 differentially-expressed miRNAs in resistant BC patients. miR-3646, miR-4741, miR-6730-3p, miR-6831-5p and miR-8485 were candidate for resistance diagnosis in BC. Logistic multiple regression analysis showed that miR-4741 (or = 0.30, 95% CI = 0.08–0.63, P = 0.02) and miR-6831-5p (or = 0.48, 95% CI = 0.24–0.78, P = 0.01) were protective factors of BC resistance. The ROC curves showed a sensitivity of 0.884 and 0.750 for miR-4741 and miR-6831-5P as markers of resistance, suggesting that they can be used as independent risk factors for BC resistance. The other 3 miRNAs can be used as calibration factors to establish the risk prediction model of resistance in BC. In risk model, the prediction accuracy of resistance of BC is about 78%. 5-miRNA signature diagnostic models can help clinicians provide personalized treatment for NAC resistance BC patients to improve patient survival. CONCLUSION: MiR-4741 and miR-6831-5p are independent risk factors for breast cancer resistance. This study constructed a nomogram model of NAC resistance in BC based on 5 differentially-expressed serum miRNAs.
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spelling pubmed-104274862023-08-17 Predictive miRNAs Patterns in Blood of Breast Cancer Patients Demonstrating Resistance Towards Neoadjuvant Chemotherapy Fan, Jingjing Tang, Yunjian Wang, Kunming Yang, Shu Ma, Binlin Breast Cancer (Dove Med Press) Original Research OBJECTIVE: The effect of chemotherapy in patients with breast cancer (BC) is uncertain. This study attempted to analyze serum microRNAs (miRNAs) in NAC resistant and sensitive BC patients and develop a miRNA-based nomogram model. To further help clinicians make treatment decisions for hormone receptor-positive patients. METHODS: A total of 110 BC patients with NAC were recruited and assigned in sensitive and resistant group, and 4 sensitive patients and 3 resistant patients were subjected to high-throughput sequencing. The functions of their target genes were analyzed by GO and KEGG. Five BC-related reported miRNAs were selected for expression pattern measurement by RT-qPCR and multivariate logistic analysis. The nomogram model was developed using R 4.0.1, and its predictive efficacy, consistency and clinical application value in development and validation groups were evaluated using ROC, calibration and decision curves. RESULTS: There were 44 differentially-expressed miRNAs in resistant BC patients. miR-3646, miR-4741, miR-6730-3p, miR-6831-5p and miR-8485 were candidate for resistance diagnosis in BC. Logistic multiple regression analysis showed that miR-4741 (or = 0.30, 95% CI = 0.08–0.63, P = 0.02) and miR-6831-5p (or = 0.48, 95% CI = 0.24–0.78, P = 0.01) were protective factors of BC resistance. The ROC curves showed a sensitivity of 0.884 and 0.750 for miR-4741 and miR-6831-5P as markers of resistance, suggesting that they can be used as independent risk factors for BC resistance. The other 3 miRNAs can be used as calibration factors to establish the risk prediction model of resistance in BC. In risk model, the prediction accuracy of resistance of BC is about 78%. 5-miRNA signature diagnostic models can help clinicians provide personalized treatment for NAC resistance BC patients to improve patient survival. CONCLUSION: MiR-4741 and miR-6831-5p are independent risk factors for breast cancer resistance. This study constructed a nomogram model of NAC resistance in BC based on 5 differentially-expressed serum miRNAs. Dove 2023-08-11 /pmc/articles/PMC10427486/ /pubmed/37593370 http://dx.doi.org/10.2147/BCTT.S415080 Text en © 2023 Fan et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Fan, Jingjing
Tang, Yunjian
Wang, Kunming
Yang, Shu
Ma, Binlin
Predictive miRNAs Patterns in Blood of Breast Cancer Patients Demonstrating Resistance Towards Neoadjuvant Chemotherapy
title Predictive miRNAs Patterns in Blood of Breast Cancer Patients Demonstrating Resistance Towards Neoadjuvant Chemotherapy
title_full Predictive miRNAs Patterns in Blood of Breast Cancer Patients Demonstrating Resistance Towards Neoadjuvant Chemotherapy
title_fullStr Predictive miRNAs Patterns in Blood of Breast Cancer Patients Demonstrating Resistance Towards Neoadjuvant Chemotherapy
title_full_unstemmed Predictive miRNAs Patterns in Blood of Breast Cancer Patients Demonstrating Resistance Towards Neoadjuvant Chemotherapy
title_short Predictive miRNAs Patterns in Blood of Breast Cancer Patients Demonstrating Resistance Towards Neoadjuvant Chemotherapy
title_sort predictive mirnas patterns in blood of breast cancer patients demonstrating resistance towards neoadjuvant chemotherapy
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10427486/
https://www.ncbi.nlm.nih.gov/pubmed/37593370
http://dx.doi.org/10.2147/BCTT.S415080
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