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Analysis of Circulating Tumor DNA to Predict Neoadjuvant Therapy Effectiveness and Breast Cancer Recurrence

PURPOSE: Real-time detection and intervention can be used as potential measures to markedly decrease breast cancer mortality. Assessment of circulating tumor DNA (ctDNA) may offer great benefits for the management of breast cancer over time. However, the use of ctDNA to predict the effectiveness of...

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Autores principales: Hao, Shuai, Tian, Wuguo, Zhao, Jianjie, Chen, Yi, Zhang, Xiaohua, Gao, Bo, He, Yujun, Luo, Donglin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Breast Cancer Society 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7462818/
https://www.ncbi.nlm.nih.gov/pubmed/32908788
http://dx.doi.org/10.4048/jbc.2020.23.e41
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author Hao, Shuai
Tian, Wuguo
Zhao, Jianjie
Chen, Yi
Zhang, Xiaohua
Gao, Bo
He, Yujun
Luo, Donglin
author_facet Hao, Shuai
Tian, Wuguo
Zhao, Jianjie
Chen, Yi
Zhang, Xiaohua
Gao, Bo
He, Yujun
Luo, Donglin
author_sort Hao, Shuai
collection PubMed
description PURPOSE: Real-time detection and intervention can be used as potential measures to markedly decrease breast cancer mortality. Assessment of circulating tumor DNA (ctDNA) may offer great benefits for the management of breast cancer over time. However, the use of ctDNA to predict the effectiveness of neoadjuvant treatment and recurrence of breast cancer has rarely been studied. METHODS: We prospectively recruited 31 breast cancer patients with 4 subtypes. Three time points were set in this study, including before any therapy (C1), during surgery (T), and six months after surgery (C2). We collected peripheral blood samples from all 31 patients at C1, tumor tissue from all 31 patients at T, and peripheral blood samples from 25 patients at C2. Targeted 727-gene panel sequencing was performed on ctDNA from all blood samples and tissue DNA from all tissue samples. Somatic mutations were detected and analyzed using a reference standard pipeline. Statistical analysis was performed to identify possible associations between ctDNA profiles and clinical outcomes. RESULTS: In total, we detected 159, 271, and 70 somatic mutations in 30 C1 samples, 31 T samples, and 12 C2 samples, respectively. We identified specific genes, such as PIK3CA, TP53, and KMT2C, which were highly mutated in the tissue samples. Furthermore, mutated KMT2C observed in ctDNA of the C2 samples may be an indicator of breast cancer recurrence. CONCLUSION: Our study highlights the potential of ctDNA analysis at different timepoints for assessing tumor progression and treatment effectiveness, as well as prediction of breast cancer recurrence.
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spelling pubmed-74628182020-09-08 Analysis of Circulating Tumor DNA to Predict Neoadjuvant Therapy Effectiveness and Breast Cancer Recurrence Hao, Shuai Tian, Wuguo Zhao, Jianjie Chen, Yi Zhang, Xiaohua Gao, Bo He, Yujun Luo, Donglin J Breast Cancer Original Article PURPOSE: Real-time detection and intervention can be used as potential measures to markedly decrease breast cancer mortality. Assessment of circulating tumor DNA (ctDNA) may offer great benefits for the management of breast cancer over time. However, the use of ctDNA to predict the effectiveness of neoadjuvant treatment and recurrence of breast cancer has rarely been studied. METHODS: We prospectively recruited 31 breast cancer patients with 4 subtypes. Three time points were set in this study, including before any therapy (C1), during surgery (T), and six months after surgery (C2). We collected peripheral blood samples from all 31 patients at C1, tumor tissue from all 31 patients at T, and peripheral blood samples from 25 patients at C2. Targeted 727-gene panel sequencing was performed on ctDNA from all blood samples and tissue DNA from all tissue samples. Somatic mutations were detected and analyzed using a reference standard pipeline. Statistical analysis was performed to identify possible associations between ctDNA profiles and clinical outcomes. RESULTS: In total, we detected 159, 271, and 70 somatic mutations in 30 C1 samples, 31 T samples, and 12 C2 samples, respectively. We identified specific genes, such as PIK3CA, TP53, and KMT2C, which were highly mutated in the tissue samples. Furthermore, mutated KMT2C observed in ctDNA of the C2 samples may be an indicator of breast cancer recurrence. CONCLUSION: Our study highlights the potential of ctDNA analysis at different timepoints for assessing tumor progression and treatment effectiveness, as well as prediction of breast cancer recurrence. Korean Breast Cancer Society 2020-07-10 /pmc/articles/PMC7462818/ /pubmed/32908788 http://dx.doi.org/10.4048/jbc.2020.23.e41 Text en © 2020 Korean Breast Cancer Society https://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Hao, Shuai
Tian, Wuguo
Zhao, Jianjie
Chen, Yi
Zhang, Xiaohua
Gao, Bo
He, Yujun
Luo, Donglin
Analysis of Circulating Tumor DNA to Predict Neoadjuvant Therapy Effectiveness and Breast Cancer Recurrence
title Analysis of Circulating Tumor DNA to Predict Neoadjuvant Therapy Effectiveness and Breast Cancer Recurrence
title_full Analysis of Circulating Tumor DNA to Predict Neoadjuvant Therapy Effectiveness and Breast Cancer Recurrence
title_fullStr Analysis of Circulating Tumor DNA to Predict Neoadjuvant Therapy Effectiveness and Breast Cancer Recurrence
title_full_unstemmed Analysis of Circulating Tumor DNA to Predict Neoadjuvant Therapy Effectiveness and Breast Cancer Recurrence
title_short Analysis of Circulating Tumor DNA to Predict Neoadjuvant Therapy Effectiveness and Breast Cancer Recurrence
title_sort analysis of circulating tumor dna to predict neoadjuvant therapy effectiveness and breast cancer recurrence
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7462818/
https://www.ncbi.nlm.nih.gov/pubmed/32908788
http://dx.doi.org/10.4048/jbc.2020.23.e41
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