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Prediction of postoperative survival of triple-negative breast cancer based on nomogram model combined with expression of HIF-1α and c-myc
The aims of this study were to explore the expression of hypoxia inducible factor-1α (HIF-1α) and c-myc protein in triple-negative breast cancer (TNBC) and its clinical prognostic significance, and to establish a prediction model for postoperative survival of TNBC based on nomogram. A total of 87 pa...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6783179/ https://www.ncbi.nlm.nih.gov/pubmed/31577739 http://dx.doi.org/10.1097/MD.0000000000017370 |
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author | Cui, Jianxiu Jiang, Hongchuan |
author_facet | Cui, Jianxiu Jiang, Hongchuan |
author_sort | Cui, Jianxiu |
collection | PubMed |
description | The aims of this study were to explore the expression of hypoxia inducible factor-1α (HIF-1α) and c-myc protein in triple-negative breast cancer (TNBC) and its clinical prognostic significance, and to establish a prediction model for postoperative survival of TNBC based on nomogram. A total of 87 patients with TNBC at the Department of Breast Surgery, Beijing Chaoyang Hospital, Capital Medical University from January 2012 to December 2015 were enrolled in this study. Immunohistochemistry was performed to detect the expression of HIF-1α and c-myc protein in breast cancer tissues. Cox regression analyses were performed to explore the correlation between HIF-1α/c-myc expression and clinical pathological parameters as well as prognosis. Receiver-operating characteristic curve was generated for cox multivariate analysis. A nomogram was generated based on the cox multivariate analysis, and a calibration curve was prepared for the nomogram to evaluate the consistency between the predicted probability of the nomogram and the actual observed probability. The stability of nomogram model was validated with an external cohort including 39 TNBC patients. The positive expression rates of HIF-1α and c-myc protein in breast cancer tissues were 41.4% (36/87) and 55.2% (48/87), respectively. HIF-1α expression was significantly correlated with age, tumor diameter, histological grade, lymph node status, and tumor TNM stage; c-myc expression was significantly associated with tumor diameter, histological grade, lymph node status, and tumor TNM stage. Cox univariate and multivariate analyses showed that HIF-1α and c-myc protein expression, histological grade, lymph node status, and tumor TNM stage were the independent risk factors for postoperative survival in TNBC patients. The AUC of prediction model was 0.843 (0.809–0.887). The nomogram could predict the probability of 3-year disease-free survival according to each patient's condition. The calibration curve displayed good agreement of the predicted probability with the actual observed probability, indicating that the nomogram model had great value of prediction. The external validation indicated the prediction model had good stability. HIF-1α-positive expression, c-myc positive expression, histological grade III, lymph node positive, and TNM stage III tumors suggested that TNBC patients had a poor prognosis. This prediction model can be used to predict postoperative survival of TNBC. |
format | Online Article Text |
id | pubmed-6783179 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
spelling | pubmed-67831792019-11-13 Prediction of postoperative survival of triple-negative breast cancer based on nomogram model combined with expression of HIF-1α and c-myc Cui, Jianxiu Jiang, Hongchuan Medicine (Baltimore) 5750 The aims of this study were to explore the expression of hypoxia inducible factor-1α (HIF-1α) and c-myc protein in triple-negative breast cancer (TNBC) and its clinical prognostic significance, and to establish a prediction model for postoperative survival of TNBC based on nomogram. A total of 87 patients with TNBC at the Department of Breast Surgery, Beijing Chaoyang Hospital, Capital Medical University from January 2012 to December 2015 were enrolled in this study. Immunohistochemistry was performed to detect the expression of HIF-1α and c-myc protein in breast cancer tissues. Cox regression analyses were performed to explore the correlation between HIF-1α/c-myc expression and clinical pathological parameters as well as prognosis. Receiver-operating characteristic curve was generated for cox multivariate analysis. A nomogram was generated based on the cox multivariate analysis, and a calibration curve was prepared for the nomogram to evaluate the consistency between the predicted probability of the nomogram and the actual observed probability. The stability of nomogram model was validated with an external cohort including 39 TNBC patients. The positive expression rates of HIF-1α and c-myc protein in breast cancer tissues were 41.4% (36/87) and 55.2% (48/87), respectively. HIF-1α expression was significantly correlated with age, tumor diameter, histological grade, lymph node status, and tumor TNM stage; c-myc expression was significantly associated with tumor diameter, histological grade, lymph node status, and tumor TNM stage. Cox univariate and multivariate analyses showed that HIF-1α and c-myc protein expression, histological grade, lymph node status, and tumor TNM stage were the independent risk factors for postoperative survival in TNBC patients. The AUC of prediction model was 0.843 (0.809–0.887). The nomogram could predict the probability of 3-year disease-free survival according to each patient's condition. The calibration curve displayed good agreement of the predicted probability with the actual observed probability, indicating that the nomogram model had great value of prediction. The external validation indicated the prediction model had good stability. HIF-1α-positive expression, c-myc positive expression, histological grade III, lymph node positive, and TNM stage III tumors suggested that TNBC patients had a poor prognosis. This prediction model can be used to predict postoperative survival of TNBC. Wolters Kluwer Health 2019-10-04 /pmc/articles/PMC6783179/ /pubmed/31577739 http://dx.doi.org/10.1097/MD.0000000000017370 Text en Copyright © 2019 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by/4.0 This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0 |
spellingShingle | 5750 Cui, Jianxiu Jiang, Hongchuan Prediction of postoperative survival of triple-negative breast cancer based on nomogram model combined with expression of HIF-1α and c-myc |
title | Prediction of postoperative survival of triple-negative breast cancer based on nomogram model combined with expression of HIF-1α and c-myc |
title_full | Prediction of postoperative survival of triple-negative breast cancer based on nomogram model combined with expression of HIF-1α and c-myc |
title_fullStr | Prediction of postoperative survival of triple-negative breast cancer based on nomogram model combined with expression of HIF-1α and c-myc |
title_full_unstemmed | Prediction of postoperative survival of triple-negative breast cancer based on nomogram model combined with expression of HIF-1α and c-myc |
title_short | Prediction of postoperative survival of triple-negative breast cancer based on nomogram model combined with expression of HIF-1α and c-myc |
title_sort | prediction of postoperative survival of triple-negative breast cancer based on nomogram model combined with expression of hif-1α and c-myc |
topic | 5750 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6783179/ https://www.ncbi.nlm.nih.gov/pubmed/31577739 http://dx.doi.org/10.1097/MD.0000000000017370 |
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