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A Three-mRNA Signature Associated with Pyrimidine Metabolism for Prognosis of BRCA
OBJECTIVE: Breast invasive carcinoma (BRCA), as a systemic disease, is currently the most malignant tumor among women. Early detection of BRCA will increase the probability of cure. Pyrimidine metabolism (PyM) stands for an essential metabolic pathway related to DNA replication of cancer cells, whic...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8866008/ https://www.ncbi.nlm.nih.gov/pubmed/35224098 http://dx.doi.org/10.1155/2022/7201963 |
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author | Zhang, Xiaoxue Zhang, Qiang Xie, Xianxin Li, Yang Pang, Zhiyuan Yu, Tao |
author_facet | Zhang, Xiaoxue Zhang, Qiang Xie, Xianxin Li, Yang Pang, Zhiyuan Yu, Tao |
author_sort | Zhang, Xiaoxue |
collection | PubMed |
description | OBJECTIVE: Breast invasive carcinoma (BRCA), as a systemic disease, is currently the most malignant tumor among women. Early detection of BRCA will increase the probability of cure. Pyrimidine metabolism (PyM) stands for an essential metabolic pathway related to DNA replication of cancer cells, which may also serve as a diagnostic marker and therapeutic target. Therefore, the aim of this research is to discover a prognostic signature associated with PyM for BRCA. METHODS: The BRCA mRNA sequencing data along with microarray data were obtained based on The Cancer Genome Atlas (TCGA) database. In addition, 4 PyM-related gene sets were profiled through gene set enrichment analysis (GSEA); it revealed the core genes differentially expressed in cancer and paracancerous tissue. Thereafter, genes were subjected to univariate as well as multivariate regression for constructing an mRNA signature to independently predict BRCA prognosis. Then, the Kaplan-Meier (KM) curve was applied for validation. The prognostic power of the signature was verified against the METABRIC (Molecular Taxonomy of Breast Cancer International Consortium) database. RESULTS: We constructed a three-mRNA (RRM2B, NME3, and POLD2) gene signature related to PyM to predict overall survival (OS) for BRCA. The as-constructed gene signature was adopted to classify cases as high- or low-risk group, identifying patients with BRCA with poor prognosis. Additionally, the risk score obtained using our constructed 3-mRNA prognosis signature is independent from other clinical variables. CONCLUSION: Our findings suggested that PyM-related mRNA signature might be a combined prognostic biomarker for BRCA and can provide important reference that are useful for individualized treatment for BRCA patients. |
format | Online Article Text |
id | pubmed-8866008 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-88660082022-02-24 A Three-mRNA Signature Associated with Pyrimidine Metabolism for Prognosis of BRCA Zhang, Xiaoxue Zhang, Qiang Xie, Xianxin Li, Yang Pang, Zhiyuan Yu, Tao Biomed Res Int Research Article OBJECTIVE: Breast invasive carcinoma (BRCA), as a systemic disease, is currently the most malignant tumor among women. Early detection of BRCA will increase the probability of cure. Pyrimidine metabolism (PyM) stands for an essential metabolic pathway related to DNA replication of cancer cells, which may also serve as a diagnostic marker and therapeutic target. Therefore, the aim of this research is to discover a prognostic signature associated with PyM for BRCA. METHODS: The BRCA mRNA sequencing data along with microarray data were obtained based on The Cancer Genome Atlas (TCGA) database. In addition, 4 PyM-related gene sets were profiled through gene set enrichment analysis (GSEA); it revealed the core genes differentially expressed in cancer and paracancerous tissue. Thereafter, genes were subjected to univariate as well as multivariate regression for constructing an mRNA signature to independently predict BRCA prognosis. Then, the Kaplan-Meier (KM) curve was applied for validation. The prognostic power of the signature was verified against the METABRIC (Molecular Taxonomy of Breast Cancer International Consortium) database. RESULTS: We constructed a three-mRNA (RRM2B, NME3, and POLD2) gene signature related to PyM to predict overall survival (OS) for BRCA. The as-constructed gene signature was adopted to classify cases as high- or low-risk group, identifying patients with BRCA with poor prognosis. Additionally, the risk score obtained using our constructed 3-mRNA prognosis signature is independent from other clinical variables. CONCLUSION: Our findings suggested that PyM-related mRNA signature might be a combined prognostic biomarker for BRCA and can provide important reference that are useful for individualized treatment for BRCA patients. Hindawi 2022-02-16 /pmc/articles/PMC8866008/ /pubmed/35224098 http://dx.doi.org/10.1155/2022/7201963 Text en Copyright © 2022 Xiaoxue Zhang et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Zhang, Xiaoxue Zhang, Qiang Xie, Xianxin Li, Yang Pang, Zhiyuan Yu, Tao A Three-mRNA Signature Associated with Pyrimidine Metabolism for Prognosis of BRCA |
title | A Three-mRNA Signature Associated with Pyrimidine Metabolism for Prognosis of BRCA |
title_full | A Three-mRNA Signature Associated with Pyrimidine Metabolism for Prognosis of BRCA |
title_fullStr | A Three-mRNA Signature Associated with Pyrimidine Metabolism for Prognosis of BRCA |
title_full_unstemmed | A Three-mRNA Signature Associated with Pyrimidine Metabolism for Prognosis of BRCA |
title_short | A Three-mRNA Signature Associated with Pyrimidine Metabolism for Prognosis of BRCA |
title_sort | three-mrna signature associated with pyrimidine metabolism for prognosis of brca |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8866008/ https://www.ncbi.nlm.nih.gov/pubmed/35224098 http://dx.doi.org/10.1155/2022/7201963 |
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