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Early Prediction of Tumor Response to Neoadjuvant Chemotherapy and Clinical Outcome in Breast Cancer Using a Novel FDG-PET Parameter for Cancer Stem Cell Metabolism

Cancer stem cells (CSCs) contribute to chemoresistance and tumor relapse. By using the distinct metabolic phenotype of CSC, we designed novel PET parameters for CSC metabolism and investigated their clinical values. Patients with breast cancer who underwent (18)F-FDG PET/CT before neoadjuvant chemot...

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Autores principales: Kim, Chanwoo, Han, Sang-Ah, Won, Kyu Yeoun, Hong, Il Ki, Kim, Deog Yoon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7565130/
https://www.ncbi.nlm.nih.gov/pubmed/32957507
http://dx.doi.org/10.3390/jpm10030132
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author Kim, Chanwoo
Han, Sang-Ah
Won, Kyu Yeoun
Hong, Il Ki
Kim, Deog Yoon
author_facet Kim, Chanwoo
Han, Sang-Ah
Won, Kyu Yeoun
Hong, Il Ki
Kim, Deog Yoon
author_sort Kim, Chanwoo
collection PubMed
description Cancer stem cells (CSCs) contribute to chemoresistance and tumor relapse. By using the distinct metabolic phenotype of CSC, we designed novel PET parameters for CSC metabolism and investigated their clinical values. Patients with breast cancer who underwent (18)F-FDG PET/CT before neoadjuvant chemotherapy (NAC) were retrospectively included. We developed a method to measure CSC metabolism using standardized uptake value histogram data. The predictive value of novel CSC metabolic parameters for pathologic complete response (pCR) was assessed with multivariable logistic regression. The association between the CSC parameter and disease-free survival (DFS) was also determined. We identified 82 patients with HER2-positive/triple-negative subtypes and 38 patients with luminal tumors. After multivariable analysis, only metabolic tumor volume for CSC (MTVcsc) among metabolic parameters remained the independent predictor of pCR (OR, 0.12; p = 0.022). MTVcsc successfully predicted pathologic tumor response to NAC in HER2-positive/triple-negative subtypes (accuracy, 74%) but not in the luminal subtype (accuracy, 29%). MTVcsc was also predictive of DFS, with a 3-year DFS of 90% in the lower MTVcsc group (<1.75 cm(3)) versus 72% in the higher group (>1.75 cm(3)). A novel data-driven PET parameter for CSC metabolism provides early prediction of pCR after NAC and DFS in HER2-positive and triple-negative subtypes.
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spelling pubmed-75651302020-10-26 Early Prediction of Tumor Response to Neoadjuvant Chemotherapy and Clinical Outcome in Breast Cancer Using a Novel FDG-PET Parameter for Cancer Stem Cell Metabolism Kim, Chanwoo Han, Sang-Ah Won, Kyu Yeoun Hong, Il Ki Kim, Deog Yoon J Pers Med Article Cancer stem cells (CSCs) contribute to chemoresistance and tumor relapse. By using the distinct metabolic phenotype of CSC, we designed novel PET parameters for CSC metabolism and investigated their clinical values. Patients with breast cancer who underwent (18)F-FDG PET/CT before neoadjuvant chemotherapy (NAC) were retrospectively included. We developed a method to measure CSC metabolism using standardized uptake value histogram data. The predictive value of novel CSC metabolic parameters for pathologic complete response (pCR) was assessed with multivariable logistic regression. The association between the CSC parameter and disease-free survival (DFS) was also determined. We identified 82 patients with HER2-positive/triple-negative subtypes and 38 patients with luminal tumors. After multivariable analysis, only metabolic tumor volume for CSC (MTVcsc) among metabolic parameters remained the independent predictor of pCR (OR, 0.12; p = 0.022). MTVcsc successfully predicted pathologic tumor response to NAC in HER2-positive/triple-negative subtypes (accuracy, 74%) but not in the luminal subtype (accuracy, 29%). MTVcsc was also predictive of DFS, with a 3-year DFS of 90% in the lower MTVcsc group (<1.75 cm(3)) versus 72% in the higher group (>1.75 cm(3)). A novel data-driven PET parameter for CSC metabolism provides early prediction of pCR after NAC and DFS in HER2-positive and triple-negative subtypes. MDPI 2020-09-17 /pmc/articles/PMC7565130/ /pubmed/32957507 http://dx.doi.org/10.3390/jpm10030132 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kim, Chanwoo
Han, Sang-Ah
Won, Kyu Yeoun
Hong, Il Ki
Kim, Deog Yoon
Early Prediction of Tumor Response to Neoadjuvant Chemotherapy and Clinical Outcome in Breast Cancer Using a Novel FDG-PET Parameter for Cancer Stem Cell Metabolism
title Early Prediction of Tumor Response to Neoadjuvant Chemotherapy and Clinical Outcome in Breast Cancer Using a Novel FDG-PET Parameter for Cancer Stem Cell Metabolism
title_full Early Prediction of Tumor Response to Neoadjuvant Chemotherapy and Clinical Outcome in Breast Cancer Using a Novel FDG-PET Parameter for Cancer Stem Cell Metabolism
title_fullStr Early Prediction of Tumor Response to Neoadjuvant Chemotherapy and Clinical Outcome in Breast Cancer Using a Novel FDG-PET Parameter for Cancer Stem Cell Metabolism
title_full_unstemmed Early Prediction of Tumor Response to Neoadjuvant Chemotherapy and Clinical Outcome in Breast Cancer Using a Novel FDG-PET Parameter for Cancer Stem Cell Metabolism
title_short Early Prediction of Tumor Response to Neoadjuvant Chemotherapy and Clinical Outcome in Breast Cancer Using a Novel FDG-PET Parameter for Cancer Stem Cell Metabolism
title_sort early prediction of tumor response to neoadjuvant chemotherapy and clinical outcome in breast cancer using a novel fdg-pet parameter for cancer stem cell metabolism
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7565130/
https://www.ncbi.nlm.nih.gov/pubmed/32957507
http://dx.doi.org/10.3390/jpm10030132
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