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Combined mRNAs and clinical factors model on predicting prognosis in patients with triple-negative breast cancer
OBJECTIVE: Triple-negative breast cancer (TNBC) is aggressive cancer usually diagnosed in young women with no effective prognosis prediction model to use. The present study was performed to develop a useful prognostic model for predicting overall survival (OS) for TNBC patients. METHODS: The Cancer...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8716048/ https://www.ncbi.nlm.nih.gov/pubmed/34965257 http://dx.doi.org/10.1371/journal.pone.0260811 |
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author | Hu, Yanjun Zou, Dehong |
author_facet | Hu, Yanjun Zou, Dehong |
author_sort | Hu, Yanjun |
collection | PubMed |
description | OBJECTIVE: Triple-negative breast cancer (TNBC) is aggressive cancer usually diagnosed in young women with no effective prognosis prediction model to use. The present study was performed to develop a useful prognostic model for predicting overall survival (OS) for TNBC patients. METHODS: The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) databases were used as training and validation data sets, respectively, in which the gene expression levels and clinical prognostic information of TNBC were collected. Differentially expressed genes (DEGs) between TNBC and non-TNBC (NTNBC) were identified with the thresholds of false discovery rate < 0.05 and |log(2) Fold Change| > 1. DEGs in AmiGO2 and the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were retained for further study. Univariate, multivariate Cox, and logistic regression analysis were conducted for detecting DEG signature with the threshold of log-rank P < 0.05. The prognosis models of mRNA signature, clinical factors were constructed and compared. RESULTS: One five-DEG signature, including CHST4, COCH, CST9, SOX11, and TDGF1 was identified in DEG prognosis model. Stratified analysis showed that the patients aged over 60, with higher pathologic stage (III-IV) and recurrence induced a significantly lower survival rate than those aged below 60, lower pathologic stage and without recurrence. Compared with patients with low-risk scores, those presented high-risk scores demonstrated significantly lower survival rate in the subgroup aged over 60 [HR = 3.780 (1.801–7.933), P < 0.0001]. For patients who obtained a higher pathologic stage and recurrence, high-risk scores were correlated with a significantly lower survival rate than patients with low-risk scores. The five-mRNA signature combined with clinical model (AUC = 0.950) predicted better than single clinical model (AUC = 0.795) or five-mRNA signature model (AUC = 0.823). CONCLUSION: Our present study identified a prognostic prediction model (combined with five-mRNA signature and clinical factors) for TNBC patients receiving immunotherapy, which will benefit future research and clinical therapies. |
format | Online Article Text |
id | pubmed-8716048 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-87160482021-12-30 Combined mRNAs and clinical factors model on predicting prognosis in patients with triple-negative breast cancer Hu, Yanjun Zou, Dehong PLoS One Research Article OBJECTIVE: Triple-negative breast cancer (TNBC) is aggressive cancer usually diagnosed in young women with no effective prognosis prediction model to use. The present study was performed to develop a useful prognostic model for predicting overall survival (OS) for TNBC patients. METHODS: The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) databases were used as training and validation data sets, respectively, in which the gene expression levels and clinical prognostic information of TNBC were collected. Differentially expressed genes (DEGs) between TNBC and non-TNBC (NTNBC) were identified with the thresholds of false discovery rate < 0.05 and |log(2) Fold Change| > 1. DEGs in AmiGO2 and the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were retained for further study. Univariate, multivariate Cox, and logistic regression analysis were conducted for detecting DEG signature with the threshold of log-rank P < 0.05. The prognosis models of mRNA signature, clinical factors were constructed and compared. RESULTS: One five-DEG signature, including CHST4, COCH, CST9, SOX11, and TDGF1 was identified in DEG prognosis model. Stratified analysis showed that the patients aged over 60, with higher pathologic stage (III-IV) and recurrence induced a significantly lower survival rate than those aged below 60, lower pathologic stage and without recurrence. Compared with patients with low-risk scores, those presented high-risk scores demonstrated significantly lower survival rate in the subgroup aged over 60 [HR = 3.780 (1.801–7.933), P < 0.0001]. For patients who obtained a higher pathologic stage and recurrence, high-risk scores were correlated with a significantly lower survival rate than patients with low-risk scores. The five-mRNA signature combined with clinical model (AUC = 0.950) predicted better than single clinical model (AUC = 0.795) or five-mRNA signature model (AUC = 0.823). CONCLUSION: Our present study identified a prognostic prediction model (combined with five-mRNA signature and clinical factors) for TNBC patients receiving immunotherapy, which will benefit future research and clinical therapies. Public Library of Science 2021-12-29 /pmc/articles/PMC8716048/ /pubmed/34965257 http://dx.doi.org/10.1371/journal.pone.0260811 Text en https://creativecommons.org/publicdomain/zero/1.0/This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication. |
spellingShingle | Research Article Hu, Yanjun Zou, Dehong Combined mRNAs and clinical factors model on predicting prognosis in patients with triple-negative breast cancer |
title | Combined mRNAs and clinical factors model on predicting prognosis in patients with triple-negative breast cancer |
title_full | Combined mRNAs and clinical factors model on predicting prognosis in patients with triple-negative breast cancer |
title_fullStr | Combined mRNAs and clinical factors model on predicting prognosis in patients with triple-negative breast cancer |
title_full_unstemmed | Combined mRNAs and clinical factors model on predicting prognosis in patients with triple-negative breast cancer |
title_short | Combined mRNAs and clinical factors model on predicting prognosis in patients with triple-negative breast cancer |
title_sort | combined mrnas and clinical factors model on predicting prognosis in patients with triple-negative breast cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8716048/ https://www.ncbi.nlm.nih.gov/pubmed/34965257 http://dx.doi.org/10.1371/journal.pone.0260811 |
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