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Construction and validation of a 6-gene nomogram discriminating lung metastasis risk of breast cancer patients

Breast cancer is the most common malignant disease in women. Metastasis is the foremost cause of death. Breast tumor cells have a proclivity to metastasize to specific organs. The lung is one of the most common sites of breast cancer metastasis. Therefore, we aimed to build a useful and convenient p...

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Autores principales: Wang, Lingchen, Wang, Wenhua, Zeng, Shaopeng, Zheng, Huilie, Lu, Quqin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7773205/
https://www.ncbi.nlm.nih.gov/pubmed/33378415
http://dx.doi.org/10.1371/journal.pone.0244693
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author Wang, Lingchen
Wang, Wenhua
Zeng, Shaopeng
Zheng, Huilie
Lu, Quqin
author_facet Wang, Lingchen
Wang, Wenhua
Zeng, Shaopeng
Zheng, Huilie
Lu, Quqin
author_sort Wang, Lingchen
collection PubMed
description Breast cancer is the most common malignant disease in women. Metastasis is the foremost cause of death. Breast tumor cells have a proclivity to metastasize to specific organs. The lung is one of the most common sites of breast cancer metastasis. Therefore, we aimed to build a useful and convenient prediction tool based on several genes that may affect lung metastasis-free survival (LMFS). We preliminarily identified 319 genes associated with lung metastasis in the training set GSE5327 (n = 58). Enrichment analysis of GO functions and KEGG pathways was conducted based on these genes. The best genes for modeling were selected using a robust likelihood-based survival modeling approach: GOLGB1, TMEM158, CXCL8, MCM5, HIF1AN, and TSPAN31. A prognostic nomogram for predicting lung metastasis in breast cancer was developed based on these six genes. The effectiveness of the nomogram was evaluated in the training set GSE5327 and the validation set GSE2603. Both the internal validation and the external validation manifested the effectiveness of our 6-gene prognostic nomogram in predicting the lung metastasis risk of breast cancer patients. On the other hand, in the validation set GSE2603, we found that neither the six genes in the nomogram nor the risk predicted by the nomogram were associated with bone metastasis of breast cancer, preliminarily suggesting that these genes and nomogram were specifically associated with lung metastasis of breast cancer. What’s more, five genes in the nomogram were significantly differentially expressed between breast cancer and normal breast tissues in the TIMER database. In conclusion, we constructed a new and convenient prediction model based on 6 genes that showed practical value in predicting the lung metastasis risk for clinical breast cancer patients. In addition, some of these genes could be treated as potential metastasis biomarkers for antimetastatic therapy in breast cancer. The evolution of this nomogram will provide a good reference for the prediction of tumor metastasis to other specific organs.
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spelling pubmed-77732052021-01-07 Construction and validation of a 6-gene nomogram discriminating lung metastasis risk of breast cancer patients Wang, Lingchen Wang, Wenhua Zeng, Shaopeng Zheng, Huilie Lu, Quqin PLoS One Research Article Breast cancer is the most common malignant disease in women. Metastasis is the foremost cause of death. Breast tumor cells have a proclivity to metastasize to specific organs. The lung is one of the most common sites of breast cancer metastasis. Therefore, we aimed to build a useful and convenient prediction tool based on several genes that may affect lung metastasis-free survival (LMFS). We preliminarily identified 319 genes associated with lung metastasis in the training set GSE5327 (n = 58). Enrichment analysis of GO functions and KEGG pathways was conducted based on these genes. The best genes for modeling were selected using a robust likelihood-based survival modeling approach: GOLGB1, TMEM158, CXCL8, MCM5, HIF1AN, and TSPAN31. A prognostic nomogram for predicting lung metastasis in breast cancer was developed based on these six genes. The effectiveness of the nomogram was evaluated in the training set GSE5327 and the validation set GSE2603. Both the internal validation and the external validation manifested the effectiveness of our 6-gene prognostic nomogram in predicting the lung metastasis risk of breast cancer patients. On the other hand, in the validation set GSE2603, we found that neither the six genes in the nomogram nor the risk predicted by the nomogram were associated with bone metastasis of breast cancer, preliminarily suggesting that these genes and nomogram were specifically associated with lung metastasis of breast cancer. What’s more, five genes in the nomogram were significantly differentially expressed between breast cancer and normal breast tissues in the TIMER database. In conclusion, we constructed a new and convenient prediction model based on 6 genes that showed practical value in predicting the lung metastasis risk for clinical breast cancer patients. In addition, some of these genes could be treated as potential metastasis biomarkers for antimetastatic therapy in breast cancer. The evolution of this nomogram will provide a good reference for the prediction of tumor metastasis to other specific organs. Public Library of Science 2020-12-30 /pmc/articles/PMC7773205/ /pubmed/33378415 http://dx.doi.org/10.1371/journal.pone.0244693 Text en © 2020 Wang et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Wang, Lingchen
Wang, Wenhua
Zeng, Shaopeng
Zheng, Huilie
Lu, Quqin
Construction and validation of a 6-gene nomogram discriminating lung metastasis risk of breast cancer patients
title Construction and validation of a 6-gene nomogram discriminating lung metastasis risk of breast cancer patients
title_full Construction and validation of a 6-gene nomogram discriminating lung metastasis risk of breast cancer patients
title_fullStr Construction and validation of a 6-gene nomogram discriminating lung metastasis risk of breast cancer patients
title_full_unstemmed Construction and validation of a 6-gene nomogram discriminating lung metastasis risk of breast cancer patients
title_short Construction and validation of a 6-gene nomogram discriminating lung metastasis risk of breast cancer patients
title_sort construction and validation of a 6-gene nomogram discriminating lung metastasis risk of breast cancer patients
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7773205/
https://www.ncbi.nlm.nih.gov/pubmed/33378415
http://dx.doi.org/10.1371/journal.pone.0244693
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